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  Document-oriented database

  A document-oriented database, or document store, is a computer program and data storage system designed for storing, retrieving, and managing document-oriented information, also known as semi-structured data. Document-oriented databases are one of the main categories of NoSQL databases, and the popularity of the term "document-oriented database" has grown alongside the adoption of NoSQL itself. XML databases are a subclass of document-oriented databases optimized for XML documents. Graph databases are similar, but add another layer, the relationship, which allows them to link documents for rapid traversal. Document-oriented databases are conceptually an extension of the key–value store, another type of NoSQL database. In key-value stores, data is treated as opaque by the database, whereas document-oriented systems exploit the internal structure of documents to extract metadata and optimize storage and queries. Although in practice the distinction can be minimal due to modern tooling, document stores are designed to provide a richer programming experience with modern programming techniques. Document databases differ significantly from traditional relational databases (RDBs). Relational databases store data in predefined tables, often requiring an object to be split across multiple tables. In contrast, document databases store all information for a given object in a single document, with each document potentially having a unique structure. This design eliminates the need for object-relational mapping when loading data into the database. == Documents == The central concept of a document-oriented database is the notion of a document. Although implementations vary in their specific definitions, document-oriented databases generally treat documents as self-contained units that encapsulate and encode data in a standardized format. Common encoding formats include XML, YAML, JSON, as well as binary representations such as BSON. Documents in a document store are equivalent to the programming concept of an object. They are not required to adhere to a fixed schema, and documents within the same collection may contain different fields or structures. Fields may be optional, and documents of the same logical type may differ in composition. For example, the following illustrates a document encoded in JSON: A second document might be encoded in XML as: The two example documents share some structural elements but also contain unique fields. The structure, text, and other data within each document are collectively referred to as the document's content and can be accessed or modified using retrieval or editing operations. Unlike relational databases, in which each record contains the same fields and unused fields are left empty, document-oriented databases do not require uniform fields across documents. This design allows new information to be added to some documents without affecting the structure of others. Document databases often support the storage of additional metadata alongside the document content. Such metadata may relate to organizational features, security, indexing, or other implementation-specific features. === CRUD operations === The core operations supported by a document-oriented database for manipulating documents are similar to those in other databases. Although terminology is not perfectly standardized, these operations are generally recognized as Create, Read, Update, and Delete (CRUD). Creation (C): Adds a new document to the database. Retrieval (R): Retrieves documents or fields based on queries. Update (U): Modifies the contents of existing documents. Deletion (D): Removes documents from the database. === Keys === Documents in a document-oriented database are addressed via a unique identifier. This identifier, often a string, URI, or path, can be used to retrieve the document from the database. Most document stores maintain an index on the key to optimize retrieval, and in some implementations the key is required when creating or inserting a new document. === Retrieval === In addition to key-based access, document-oriented databases typically provide an API or query language that enables retrieval based on document content or associated metadata. For example, a query may return all documents with a specific field matching a given value. The available query features, indexing options, and performance characteristics vary across implementations. Document stores differ from key-value stores in that they exploit the internal structure and metadata of stored documents. In many key-value stores, values are treated as opaque or "black-box" data, meaning the database system does not interpret their internal structure. By contrast, document-oriented databases can classify and interpret document content. This enables queries that distinguish between types of data––for example, retrieving all phone numbers containing "555" without also matching a postal code such as "55555." === Editing === Document databases typically provide mechanisms for updating or editing the content or metadata of a document. Updates may involve replacing the entire document or modifying individual elements or fields within the document. === Organization === Document database implementations support a variety of methods for organizing documents, including: Collections: Groups of documents. Depending on the implementation, a document may be required to belong to a single collection or may be allowed in multiple collections. Tags and non-visible metadata: Additional data stored outside the main document content. Directory hierarchies: Documents organized in a tree-like structure, often based on path or URI. These organizational structures may differ between logical and physical representations (e.g. on disk or in memory). == Relationship to other databases == === Relationship to key-value stores === A document-oriented database can be viewed as a specialized form of key-value store, which is itself a category of NoSQL database. In a basic key-value store, the stored value is typically treated as opaque by the database system. By contrast, a document-oriented database provides APIs or a query and update language that allows queries and modifications based on the internal structure of the document. For users who do not require advanced query, retrieval, or update capabilities, the distinction between document-oriented databases and key-value stores may be minimal. === Relationship to search engines === Some search engine and information retrieval systems, such as Apache Solr and Elasticsearch, provide document storage and support core document operations. As a result, they may meet certain functional definitions of a document-oriented database, although their primary design goals differ. === Relationship to relational databases === In a relational database, data is organized into predefined types represented as tables. Each table contains rows (records) with a fixed set of columns (fields), so all records in a table share the same structure. Administrators typically define indexes on selected fields to improve query performance. A central principle of relational database design is database normalization, in which data that might otherwise be repeated is stored in separate tables and linked using keys. When records in different tables are related, a foreign key is used to associate them. For example, an address book application may store a contact's name, image, phone numbers, mailing addresses, and email addresses. In a normalized relational design, separate tables might be created for contacts, phone numbers, and email addresses. The phone number table would include a foreign key referencing the associated contact. To reconstruct a complete contact record, the database retrieves related information from each table using the foreign keys and combines it into a single record. In contrast, a document-oriented database stores all data related to an object within a single document, and stored in the database as a single entry. In the address book example,the contact's name, image, and contact information may be stored together in one document. The document is retrieved using a unique key, and all related information is returned together, without needing to look up multiple tables. A key difference between the document-oriented and relational models is that the data formats are not predefined in the document case. In most cases, any sort of document can be stored in a database, and documents can change in type and form over time. For example, a new field such as COUNTRY_FLAG can be added to new documents as they are inserted without affecting existing documents. To aid retrieval, document-oriented systems generally allow the administrator to provide hints to the database for locating certain types of information. These hints work in a similar fashion to indexes in relational databases. Many systems also allow additional metadata outside the content of the document itself

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  Computer-aided software engineering

  Computer-aided software engineering (CASE) is a domain of software tools used to design and implement applications. CASE tools are similar to and are partly inspired by computer-aided design (CAD) tools used for designing hardware products. CASE tools are intended to help develop high-quality, defect-free, and maintainable software. CASE software was often associated with methods for the development of information systems together with automated tools that could be used in the software development process. == History == The Information System Design and Optimization System (ISDOS) project, started in 1968 at the University of Michigan, initiated a great deal of interest in the whole concept of using computer systems to help analysts in the very difficult process of analysing requirements and developing systems. Several papers by Daniel Teichroew fired a whole generation of enthusiasts with the potential of automated systems development. His Problem Statement Language / Problem Statement Analyzer (PSL/PSA) tool was a CASE tool although it predated the term. Another major thread emerged as a logical extension to the data dictionary of a database. By extending the range of metadata held, the attributes of an application could be held within a dictionary and used at runtime. This "active dictionary" became the precursor to the more modern model-driven engineering capability. However, the active dictionary did not provide a graphical representation of any of the metadata. It was the linking of the concept of a dictionary holding analysts' metadata, as derived from the use of an integrated set of techniques, together with the graphical representation of such data that gave rise to the earlier versions of CASE. The next entrant into the market was Excelerator from Index Technology in Cambridge, Mass. While DesignAid ran on Convergent Technologies and later Burroughs Ngen networked microcomputers, Index launched Excelerator on the IBM PC/AT platform. While, at the time of launch, and for several years, the IBM platform did not support networking or a centralized database as did the Convergent Technologies or Burroughs machines, the allure of IBM was strong, and Excelerator came to prominence. Hot on the heels of Excelerator were a rash of offerings from companies such as Knowledgeware (James Martin, Fran Tarkenton and Don Addington), Texas Instrument's CA Gen and Andersen Consulting's FOUNDATION toolset (DESIGN/1, INSTALL/1, FCP). CASE tools were at their peak in the early 1990s. According to the PC Magazine of January 1990, over 100 companies were offering nearly 200 different CASE tools. At the time IBM had proposed AD/Cycle, which was an alliance of software vendors centered on IBM's Software repository using IBM DB2 in mainframe and OS/2: The application development tools can be from several sources: from IBM, from vendors, and from the customers themselves. IBM has entered into relationships with Bachman Information Systems, Index Technology Corporation, and Knowledgeware wherein selected products from these vendors will be marketed through an IBM complementary marketing program to provide offerings that will help to achieve complete life-cycle coverage. With the decline of the mainframe, AD/Cycle and the Big CASE tools died off, opening the market for the mainstream CASE tools of today. Many of the leaders of the CASE market of the early 1990s ended up being purchased by Computer Associates, including IEW, IEF, ADW, Cayenne, and Learmonth & Burchett Management Systems (LBMS). The other trend that led to the evolution of CASE tools was the rise of object-oriented methods and tools. Most of the various tool vendors added some support for object-oriented methods and tools. In addition new products arose that were designed from the bottom up to support the object-oriented approach. Andersen developed its project Eagle as an alternative to Foundation. Several of the thought leaders in object-oriented development each developed their own methodology and CASE tool set: Jacobson, Rumbaugh, Booch, etc. Eventually, these diverse tool sets and methods were consolidated via standards led by the Object Management Group (OMG). The OMG's Unified Modelling Language (UML) is currently widely accepted as the industry standard for object-oriented modeling. == CASE software == === Tools === CASE tools support specific tasks in the software development life-cycle. They can be divided into the following categories: Business and analysis modeling: Graphical modeling tools. E.g., E/R modeling, object modeling, etc. Development: Design and construction phases of the life-cycle. Debugging environments. E.g., IISE LKO. Verification and validation: Analyze code and specifications for correctness, performance, etc. Configuration management: Control the check-in and check-out of repository objects and files. E.g., SCCS, IISE. Metrics and measurement: Analyze code for complexity, modularity (e.g., no "go to's"), performance, etc. Project management: Manage project plans, task assignments, scheduling. Another common way to distinguish CASE tools is the distinction between Upper CASE and Lower CASE. Upper CASE Tools support business and analysis modeling. They support traditional diagrammatic languages such as ER diagrams, Data flow diagram, Structure charts, Decision Trees, Decision tables, etc. Lower CASE Tools support development activities, such as physical design, debugging, construction, testing, component integration, maintenance, and reverse engineering. All other activities span the entire life-cycle and apply equally to upper and lower CASE. === Workbenches === Workbenches integrate two or more CASE tools and support specific software-process activities. Hence they achieve: A homogeneous and consistent interface (presentation integration) Seamless integration of tools and toolchains (control and data integration) An example workbench is Microsoft's Visual Basic programming environment. It incorporates several development tools: a GUI builder, a smart code editor, debugger, etc. Most commercial CASE products tended to be such workbenches that seamlessly integrated two or more tools. Workbenches also can be classified in the same manner as tools; as focusing on Analysis, Development, Verification, etc. as well as being focused on the upper case, lower case, or processes such as configuration management that span the complete life-cycle. === Environments === An environment is a collection of CASE tools or workbenches that attempts to support the complete software process. This contrasts with tools that focus on one specific task or a specific part of the life-cycle. CASE environments are classified by Fuggetta as follows: Toolkits: Loosely coupled collections of tools. These typically build on operating system workbenches such as the Unix Programmer's Workbench or the VMS VAX set. They typically perform integration via piping or some other basic mechanism to share data and pass control. The strength of easy integration is also one of the drawbacks. Simple passing of parameters via technologies such as shell scripting can't provide the kind of sophisticated integration that a common repository database can. Fourth generation: These environments are also known as 4GL standing for fourth generation language environments due to the fact that the early environments were designed around specific languages such as Visual Basic. They were the first environments to provide deep integration of multiple tools. Typically these environments were focused on specific types of applications. For example, user-interface driven applications that did standard atomic transactions to a relational database. Examples are Informix 4GL, and Focus. Language-centered: Environments based on a single often object-oriented language such as the Symbolics Lisp Genera environment or VisualWorks Smalltalk from Parcplace. In these environments all the operating system resources were objects in the object-oriented language. This provides powerful debugging and graphical opportunities but the code developed is mostly limited to the specific language. For this reason, these environments were mostly a niche within CASE. Their use was mostly for prototyping and R&D projects. A common core idea for these environments was the model–view–controller user interface that facilitated keeping multiple presentations of the same design consistent with the underlying model. The MVC architecture was adopted by the other types of CASE environments as well as many of the applications that were built with them. Integrated: These environments are an example of what most IT people tend to think of first when they think of CASE. Environments such as IBM's AD/Cycle, Andersen Consulting's FOUNDATION, the ICL CADES system, and DEC Cohesion. These environments attempt to cover the complete life-cycle from analysis to maintenance and provide an integrated database repository for storing all artifacts of the software pr

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  Hike Messenger

  Hike Messenger, aka Hike Sticker Chat, is a multifunctional Indian social media and social networking service offering instant messaging (IM) and Voice over IP (VoIP) services that was launched on December 11, 2012, by Kavin Bharti Mittal. Hike functioned through SMS. The app registration used a s‍tandard, one-time password (OTP) based authentication process. It was estimated to be worth $1.4 billion and had more than 100 million registered users. It went defunct on January 6, 2021, as they were unable to compete with global messaging platforms. The app re-appeared on google play store and apple app store on 19 September 2025. == History == Hike Messenger was launched on December 12, 2012, by its founder, Kavin Bharti Mittal. The majority of users were from India, with 80% under the age of 25. The company purchased startups like TinyMogul and Hoppr in 2015. After buying US-based free voice calling company Zip Phones, Hike provided VoIP calling services. On March 5, 2015, Hike launched the 'Great Indian Sticker Challenge' to create more stickers. In February 2017, Hike acquired the social networking app Pulse. From version 5.0, it became the first social messaging app to start a mobile payment service in India. The timeline feature came back after multiple user requests and the introduction of a personalized digital envelope called Blue Packets for sending monetary gifts through a built-in wallet. In 2017, the acquisition of Bengaluru-based startup Creo was announced to enable third-party developers to build services on top of the Hike platform. In 2018, Hike provided 1 billion users with internet access by targeting smaller cities. In January 2019, the company discarded the previous super-app approach, and began launching specialized apps for specific use-cases. In May 2019, Hike announced a collaboration with Indraprastha Institute of Information Technology, Delhi (IIIT-D) to develop a variety of machine learning models. In April 2019, the company launched its first standalone app, Hike Sticker Chat. A separate content app Hike News & Content was also launched. In 2021, Hike shut down its messaging service and shifted focus to gaming and community platforms. It launched Rush, a real-money gaming app featuring casual titles like ludo and carrom, which scaled to over 10 million users and generated more than US$500 million in gross revenue over four years. The company also introduced Vibe, an approval-only community app, as part of its pivot away from the super-app and messaging model. In September 2025, following the passage of the Promotion and Regulation of Online Gaming Act, which banned real-money gaming in India, Hike announced its complete closure. Founder Kavin Bharti Mittal stated that while the company had begun international expansion, scaling globally under the new regulatory regime would require a full reset that was not a viable use of capital or resources. On 19 September 2025, hike was relaunched on play store and app store by the name hike messenger. == Application == === Timeline of Features === On 15 April 2014, Hike introduced unlimited free SMS via a service called Hike Offline, through credits earned by users from regular chatting, as connectivity is still a major issue in many parts of India. In an attempt to appeal to its younger users, Hike introduced features that find resonance with the local market, such as Last Seen Privacy and localized sticker packs. It also introduced a two-way chat theme, allowing users to change the chat background for themselves and for their friends simultaneously. The app also started showing live Cricket scores in collaboration with Cricbuzz, as well as news, casual games, and social media feeds. Hike also added a file transfer service, allowing files less than 100MB of all formats, with a view on further increasing the size limit to 1 GB. With the launch of version 2.9.2.0 in January 2015, Hike implemented support for sending uncompressed images and a "quick upload" feature optimized for 2G speed. Later that month, Hike introduced a voice calling feature for its users. In September 2015, Hike launched free group call support with up to 100 people in a simultaneous conference call environment. In November 2016, Hike announced the launch of a feature called Stories that allows people to share real-life moments using fun live filters which automatically get deleted after 48 hours, and a new camera design with localized filters. Hike 4.0 launched on 26 August 2015 with the tagline 'Got a Gang? Get on Hike'. Hike 4.0 was an optimization-focused update, increasing the performance of the app on poor networks. It supported photo filters, doodles, and bite-sized news updates in under 100 characters. Hike launched News Feed with Hindi language support on 29 September 2015 to cater for the needs of the non-English population. Hike launched version 3.5 as the biggest update for Windows Phone 8.1 during December 2015 which changed the user interface for more simpler navigation, supported sending unlimited non-media files and documents of any format and better group admin settings. It also included ten brand new chat themes. Hike launched a microapp feature which was live for two days on 8 May 2016, as a Mother's Day special in which users could add images, quotes or messages as a token of love with customized e-cards and stickers on their timeline not only on Hike, but also on other platforms. On 26 October 2016, Hike Messenger rolled out the beta version of a video calling feature ahead of WhatsApp starting with the Android users which also lets recipients preview a video call before deciding to take it and is optimized to even work under 2G conditions. On 24 December 2016, Hike rolled out a short 20-second Video Stories feature that can be directly shared with friends or posted on a public timeline with different filters in collaboration with content creators with the same 48-hour time limit before being automatically deleted. The Stories feature continues to receive constant future updates to include and enable content, public story option, private user messaging and geo-tagging. In September 2017, Hike launched personalized sticker packs with 20,000+ graphical stickers for over 500 colleges that covered around 1,000 colleges by December 2018 across India which can be used across different geographies, and are highly customized for users with availability in 40+ local languages that support automatic sticker suggestions where the application suggests the best reply for any sticker message and also allows users to "nudge", a feature used to ping the receiver. Hike started supporting user comments on friend's posts, added a specific message reply function, a redesigned camera interface to support front flash and user mentions with the help of the @ symbol. In December, 2017, Hike launched group voting, bill splitting, checklists and event reminders for group chat that supports up to 1,000 users both on iOS and Android platform. Hike launched another feature called Hike Land, which is a virtual world with beta trial to start from March 2020, that will use Hike Moji where online users with their digital avatar can hang out with other users and will be built inside the Hike Sticker Chat application. It is mainly targeted but not restricted towards 16 to 21 years age group of people. Without unveiling much about Hike Land, a separate website has been created with option to reserve spots by giving details like name, gender and phone number that will link the user profile from the Hike Sticker Chat account though it is not a necessity. ==== Hike Direct ==== The Hike Direct feature is based on the technology known as WiFi Direct, which initially was also called WiFi P2P and got introduced to users by October 2015, which enables sharing of files such as music, apps, videos without a live internet connection within a 100-meter radius by creating a wireless network between two or more devices with a transfer speed of 100MB per minute. For privacy and security reasons, Hike didn't show the recipient's location or proximity and works only when two users are connected in the same room by adding one another into the contact list. ==== Hike Wallet ==== In June 2017, Hike announced the launch of version 5.0 with multiple new features like User Chat Themes, Night Mode and Magic Selfie. along with a built-in Wallet partnered with Yes Bank. This feature was first rolled out to Android users followed by iOS users at a later stage. Hike collaborated with Airtel Payment Bank to power its digital payment wallet by November 2017 where Hike users have access to Airtel Payments Bank's merchant & utility payment services and know your customer (KYC) infrastructure with 5 million transactions happening from services like recharge and P2P. Hike formed a partnership with Ola Cabs to bring a taxi and auto-rickshaw booking facility from 14 February 2018. With Hike Wallet facility users could now book bus tickets with 3

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  Story (social media)

  In social media, a story is a function in which the user tells a narrative or provides status messages and information in the form of short, time-limited clips in an automatically running sequence. == Definition == A story is a short sequence of images, videos, or other social media content, which can be accompanied by backgrounds, music, text, stickers, animations, filters or emojis. Social media platforms typically advance through the sequence automatically when presenting a story to a viewer. Although the sequential nature of stories can be used to tell a narrative, the pieces of a story can also be unrelated. Social media platforms that offer stories will typically have a primary story for each user which consists of everything the user posted to their story over a certain period of time, usually the most recent 24 hours. Most stories cannot be changed afterwards and are only available for a short time. Stories are almost exclusively created on a mobile device such as a smartphone or tablet computer and are usually displayed vertically. == History == In October 2013, Snapchat first introduced the story function as a series of Snaps that can together tell a narrative through a chronological order, with each Snap being viewable by all of the poster's friends and deleted after 24 hours. Stories soon surpassed private Snaps to become Snapchat's most-viewed type of post. After 2015, Snapchat introduced a feature allowing users to post private stories viewable by a chosen subset of their friends. Later other apps would copy this feature. In August 2016, Instagram introduced a stories function that deletes the content after 24 hours. Various commenters have accused the site of copying Snapchat. In February 2017, the instant messenger WhatsApp introduced the Now Status stories function in beta, which was later renamed Status. In March 2017, a story function was introduced in Facebook Messenger. In February 2018, Google launched AMP Stories, bringing a story-style format to certain Google search results on mobile devices. In August 2018, YouTube introduced a stories function that initially was limited to pictures, but was later expanded to support short video clips. The feature was shut down in June 2023. In August 2018, the GIF website Giphy introduced a story function. In March 2022, TikTok added a story feature which allowed users to create 15 second long videos that delete after 24 hours. In June 2023, Telegram CEO Pavel Durov announced stories for Telegram would be released in July 2023. In July 2023, the feature was released for premium users, and in August 2023 it was rolled out for all users. == User motivations == In 2022, a study performed by Jia-Dai (Evelyn) Lu and Jhih-Syuan (Elaine) Lin examined the various motivations for updating stories on Instagram. The researchers found a new configuration of motivations for using Instagram Stories: exploration, self-enhancement, perceived functionality, entertainment, social sharing, relationship building, novelty, and surveillance. The findings also highlighted that contribution and creation activities are likely to result in positive emotions, while creation alone predicts negative emotions while updating stories on Instagram. == Usage statistics == In 2019, around 1.5 billion people worldwide every day on average used the stories function in a social network or messenger. Younger people in particular use this function. More than 20% of people aged 18 to 24 use Instagram stories, while it is just under 2% of those over 55. In a Facebook survey of 18,000 participants from 12 countries, 68% said they used the stories function at least once a month. Stories in the areas of fashion and tourism are particularly popular. The website Fanpage Karma analyzed several Instagram accounts and determined the average reach of posts and stories per follower, concluding that posts have a higher reach than stories, which often have less than half the reach.

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  Outline of computer security

  The following outline is provided as an overview of and topical guide to computer security: Computer security (also cybersecurity, digital security, or information technology (IT) security) is a subdiscipline within the field of information security. It focuses on protecting computer software, systems, and networks from threats that can lead to unauthorized information disclosure, theft, or damage to hardware, software, or data, as well as to the disruption or misdirection of the services they provide. The growing significance of computer security reflects the increasing dependence on computer systems, the Internet, and evolving wireless network standards. This reliance has expanded with the proliferation of smart devices, including smartphones, televisions, and other components of the Internet of things (IoT). (yes) == Essence of computer security == Computer security can be described as all of the following: a branch of security Network security application security == Areas of computer security == Access control – selective restriction of access to a place or other resource. The act of accessing may mean consuming, entering, or using. Permission to access a resource is called authorization. Computer access control – includes authorization, authentication, access approval, and audit. Authentication Knowledge-based authentication Integrated Windows Authentication Password Password length parameter Secure Password Authentication Secure Shell Kerberos (protocol) SPNEGO NTLMSSP AEGIS SecureConnect TACACS Cyber security and countermeasure Device fingerprint Physical security – protecting property and people from damage or harm (such as from theft, espionage, or terrorist attacks). It includes security measures designed to deny unauthorized access to facilities, (such as a computer room), equipment (such as your computer), and resources (like the data storage devices, and data, in your computer). If a computer gets stolen, then the data goes with it. In addition to theft, physical access to a computer allows for ongoing espionage, like the installment of a hardware keylogger device, and so on. Data security – protecting data, such as a database, from destructive forces and the unwanted actions of unauthorized users. Information privacy – relationship between collection and dissemination of data, technology, the public expectation of privacy, and the legal and political issues surrounding them. Privacy concerns exist wherever personally identifiable information or other sensitive information is collected and stored – in digital form or otherwise. Improper or non-existent disclosure control can be the root cause for privacy issues. Internet privacy – involves the right or mandate of personal privacy concerning the storing, repurposing, provision to third parties, and displaying of information pertaining to oneself via the Internet. Privacy can entail either Personally Identifying Information (PII) or non-PII information such as a site visitor's behavior on a website. PII refers to any information that can be used to identify an individual. For example, age and physical address alone could identify who an individual is without explicitly disclosing their name, as these two factors relate to a specific person. Mobile security – security pertaining to smartphones, especially with respect to the personal and business information stored on them. Network security – provisions and policies adopted by a network administrator to prevent and monitor unauthorized access, misuse, modification, or denial of a computer network and network-accessible resources. Network security involves the authorization of access to data in a network, which is controlled by the network administrator. Network Security Toolkit Internet security – computer security specifically related to the Internet, often involving browser security but also network security on a more general level as it applies to other applications or operating systems on a whole. Its objective is to establish rules and measures to use against attacks over the Internet. The Internet represents an insecure channel for exchanging information leading to a high risk of intrusion or fraud, such as phishing. Different methods have been used to protect the transfer of data, including encryption. World Wide Web Security – dealing with the vulnerabilities of users who visit websites. Cybercrime on the Web can include identity theft, fraud, espionage and intelligence gathering. For criminals, the Web has become the preferred way to spread malware. == Computer security threats == Methods of Computer Network Attack and Computer Network Exploitation Social engineering is a frequent method of attack, and can take the form of phishing, or spear phishing in the corporate or government world, as well as counterfeit websites. Password sharing and insecure password practices Poor patch management Computer crime – Computer criminals – Hackers – in the context of computer security, a hacker is someone who seeks and exploits weaknesses in a computer system or computer network. Password cracking – Software cracking – Script kiddies – List of computer criminals – Identity theft – Computer malfunction – Operating system failure and vulnerabilities Hard disk drive failure – occurs when a hard disk drive malfunctions and the stored information cannot be accessed with a properly configured computer. A disk failure may occur in the course of normal operation, or due to an external factor such as exposure to fire or water or high magnetic fields, or suffering a sharp impact or environmental contamination, which can lead to a head crash. Data recovery from a failed hard disk is problematic and expensive. Backups are essential Computer and network surveillance – Man in the Middle Loss of anonymity – when one's identity becomes known. Identification of people or their computers allows their activity to be tracked. For example, when a person's name is matched with the IP address they are using, their activity can be tracked thereafter by monitoring the IP address. HTTP Cookie Local Shared Object Web bug Spyware Adware Cyber spying – obtaining secrets without the permission of the holder of the information (personal, sensitive, proprietary or of classified nature), from individuals, competitors, rivals, groups, governments and enemies for personal, economic, political or military advantage using methods on the Internet, networks or individual computers through the use of cracking techniques and malicious software including Trojan horses and spyware. It may be done online from by professionals sitting at their computer desks on bases in far away countries, or it may involve infiltration at home by computer trained conventional spies and moles, or it may be the criminal handiwork of amateur malicious hackers, software programmers, or thieves. Computer and network eavesdropping Lawful Interception War Driving Packet analyzer (aka packet sniffer) – mainly used as a security tool (in many ways, including for the detection of network intrusion attempts), packet analyzers can also be used for spying, to collect sensitive information (e.g., login details, cookies, personal communications) sent through a network, or to reverse engineer proprietary protocols used over a network. One way to protect data sent over a network such as the Internet is by using encryption software. Cyberwarfare – Exploit – piece of software, a chunk of data, or a sequence of commands that takes advantage of a bug, glitch or vulnerability in order to cause unintended or unanticipated behavior to occur on computer software, hardware, or something electronic (usually computerized). Such behavior frequently includes things like gaining control of a computer system, allowing privilege escalation, or a denial-of-service attack. Trojan Computer virus Computer worm Denial-of-service attack – an attempt to make a machine or network resource unavailable to its intended users, usually consisting of efforts to temporarily or indefinitely interrupt or suspend services of a host connected to the Internet. One common method of attack involves saturating the target machine with external communications requests, so much so that it cannot respond to legitimate traffic, or responds so slowly as to be rendered essentially unavailable. Distributed denial-of-service attack (DDoS) – DoS attack sent by two or more persons. Hacking tool Malware Computer virus Computer worm Keylogger – program that does keystroke logging, which is the action of recording (or logging) the keys struck on a keyboard, typically in a covert manner so that the person using the keyboard is unaware that their actions are being monitored. There are also HID spoofing hardware keyloggers, like a USB device inserting stored keystores when connected. Rootkit – stealthy type of software, typically malicious, designed to hide the existence of certain processes or programs from normal methods of detection and enable contin

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  Experimental SAGE Subsector

  The Experimental Semi-Automatic Ground Environment (SAGE) Sector (ESS, Experimental SAGE Subsector until planned Sectors/Subsectors were renamed NORAD Regions, Divisions, and Sectors) was a prototype Cold War Air Defense Sector for developing the Semi Automatic Ground Environment. The Lincoln Laboratory control center in a new building was at Lexington, Massachusetts. == ESS Computer System == The network's Direction Center was completed in a new 1954 building (Building F, 42°27′37″N 071°16′04″W) with prototype peripherals and a single IBM XD-1 computer, a successor to Lincoln Lab's Whirlwind I computer (WWI). In 1955, Air Force personnel began IBM training at the Kingston, New York, prototype facility, and the "4620th Air Defense Wing (experimental SAGE) was established at Lincoln Laboratory"—its "primary mission was computer programming". ESS had a capacity of 48 tracks and used a pre-SAGE ground environment in a "prototype intercept monitor room [at] MIT's Barta building" with "track situation displays, which geographically showed Air Defense Identification Zone lines and antiaircraft circles [and] each console also had a 5-inch CRT for digital information display. Audible alert signals were used, with a different signal for each symbol on a situation display." == Radar stations == Initial service test models of the Burroughs AN/FST-2 Coordinate Data Transmitting Set were placed with radars at South Truro and West Bath, Maine; followed by Texas Tower#2 (TT2) in the Atlantic Ocean, which provided a "triangular pattern with overlap" radar coverage (TT2 later had a connection from the XD-1 via the GE G/A Data Link Output Subsystem through North Truro Air Force Station.) By August 1955, 13 radar stations were networked by the subsector, e.g.: Chatham Clinton, Massachusetts with gap-filler radar Great Boars Head Halibut Point Killingly, Connecticut (41.865734°N 71.820958°W / 41.865734; -71.820958).with gap-filler radar Rockport Air Force Station Scituate, Massachusetts South Truro West Bath, Maine (43°54′7″N 69°50′43″W) with AN/FPS-31 on Jug Handle Hill: ("Lincoln Laboratories experimental radar station") Required by 21 November 1955 were 44 consoles: 38 for the operations floor, 3 on the computer floor for display maintenance, and 3 near the maintenance console (program checkout). WWI was connected to the Experimental SAGE Subsector to verify crosstelling (collateral communication) with the ESS DC, and WWI was also used for a Ground-to-Air (G/A) experiment using a transmitter of the GE G/A Data Link Output Subsystem on Prospect Hill, Waltham, MA sending data to simulated airborne equipment at Lexington. Transmissions from the WWI SAGE Evaluation (WISE) computer system to XD-1 and back were without error by December 1955 when operational software specifications were frozen. Operating procedures for the ESS external sites were complete in March 1956, and == System Operation Testing == From November 15, 1955, to November 7, 1956, three System Operation Tests were conducted which used voice "Ground-to-Air" communication from the Barta control room to aircraft outfitted with SAGE receivers (F-86 interceptors modified to F-86L models in "Project FOLLOW-ON".) Test teams included employees of Bell Telephone Laboratories, Western Electric-ADES, IBM, the RAND Corporation, and Lincoln Labs' Division 6, Division 3, & Division 2 (Division 6 had been created for ESS support.) The North Truro P-10 AN/FST-2 was moved to Almaden Air Force Station (M-96)c. 1957-8 and on August 7, 1958, control of an airborne BOMARC missile that had malfunctioned transferred from the "Experimental SAGE Sector" to a Westinghouse AN/GPA-35 Ground Environment system and the missile crashed into the Atlantic Ocean. By December 31, 1958, ADC Manual 55-28 described the Model 3 SAGE System. == 1959 Experimental Testing == "To prove out the revised SAGE computer program" for Automatic Targeting and Battery Evaluation and ADDC-AADCP crosstelling, a "SAGE/Missile Master" test was conducted beginning in September 1959 with communications between the ESS XD-1 and Martin AN/FSG-1 Antiaircraft Defense System equipment at Fort Banks planned for the CONAD Joint Control Center at Fort Heath—a "SAGE ATABE Simulation Study" (SASS) was also completed 1959–60 by MITRE Corporation.

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  Instagram face

  Instagram face is a beauty standard based on the filters and influencers popular on Instagram. == Overview == An "Instagram face" has catlike eyes, long lashes, a small nose, high cheekbones, full lips, and a blank expression. Digital filters manipulate photographs and video to create an idealized image that, according to critics, has resulted in an unrealistic and homogeneous beauty standard. According to Jia Tolentino, the face is "distinctly white but ambiguously ethnic". The face has been described as a racial composite of different peoples. In 2024, cosmetic surgeon Paul Banwell said, "People used to come to see me asking to look like a particular celebrity, but many patients come to me now wanting to look like the filtered version of themselves." While based on digital filters, the look is achieved in person using heavy applications of makeup or cosmetic surgery. Plastic surgery, Botox injections, and injectable filler have significantly increased in popularity since the rise of digital filters. Influencers market makeup products designed to recreate the look. == History == The growth of reality television series and social media throughout the 2010s has influenced the popularity of Instagram face. In 2019, The New Yorker referred to this phenomenon as "Instagram Face," identifying Kim Kardashian as its "patient zero." Similarly, her younger sister Kylie Jenner significantly impacted the trend with her 2015 lip filler confession, which acted as a catalyst, introducing Juvéderm to a new generation. Sirin Kale of Vice News has described Jenner as "at the vanguard of an aesthetic that’s swept through British towns and cities," while also pointing towards other celebrities such as Iggy Azalea and Farrah Abraham. In 2018, Americans underwent 7 million neurotoxin injections and 2.5 million filler injections and spent $16.5 billion on cosmetic surgery. 92% of the latter was performed on women. Botox usage has also been on the rise. == Criticism == In her 2021 book The Selfie, Temporality, and Contemporary Photography, Claire Raymond of Princeton University criticised "Instagram faces" for erasing "heritable quirks and lived history; it erases what makes the human face so compelling, whether conventionally beautiful or not," while also arguing that the procedures used to create Instagram faces "numb and freeze the face and skin, rendering less mobile the lips, the eyes, and the neck. Numbness is the central feature of the experience for the woman who gets Instagram face through cosmetic procedures. Others may see her more, but she feels less and less." == Influence on popular culture == The increasing popularity of cosmetic surgeries towards a homogeneous ideal has resulted in the emergence of the "goopcore" sub-genre of body horror. The sub-genre combines graphic violence with body modifications from the beauty industry. Allie Rowbottom's goopcore novel Aesthetica centers around an influencer attempting to undo years of plastic surgery with a new experimental procedure.

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  Social recruiting

  Social recruiting (social hiring or social media recruitment) is recruiting candidates by using social platforms as talent databases or for advertising. Social recruiting uses social media profiles, blogs, and other Internet sites to find information on candidates. It also uses social media to advertise jobs either through HR vendors or through crowdsourcing where job seekers and others share job openings within their online social networks. Social recruiting's effectiveness and return on investment have been difficult to determine, since applicants do not usually apply through the social channels which first attracted them. In May 2013, Maximum Employment Marketing Group released the Social Recruitment Monitor, which ranks the reach, engagement, and interactivity of employers' social recruiting efforts around the world. == Social recruitment software == The social recruitment software market (a form of e-recruitment) is often included in the wider talent management software sector. Bersin & Associates valued the wider talent management market at over $2bn in 2007. Social recruitment increasingly sits at an intersection of a number of fast-moving areas including social networking, recruitment and now cloud computing. Additionally, mobile recruiting has become another hot topic, especially with the rise in tablet and smartphone usage. In 2012, there was a rise of tech companies using social recruiting applications to find and screen applicants. As more companies saw value in filling jobs by putting them on the social platforms where millions of people spend at least 37 minutes daily, there developed a much larger focus on social recruiting among the talent acquisition community. By mid-2013, many major enterprise companies such as Pepsi, Gap, AIG, and Oracle had begun effectively utilizing social recruiting software, making it clear that large corporations were open to automating or streamlining (and ultimately investing in) their social recruiting processes.

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  Image subtraction

  Image subtraction or pixel subtraction or difference imaging is an image processing technique whereby the digital numeric value of one pixel or whole image is subtracted from another image, and a new image generated from the result. This is primarily done for one of two reasons – levelling uneven sections of an image such as half an image having a shadow on it, or detecting changes between two images. This method can show things in the image that have changed position, brightness, color, or shape. For this technique to work, the two images must first be spatially aligned to match features between them, and their photometric values and point spread functions must be made compatible, either by careful calibration, or by post-processing (using color mapping). The complexity of the pre-processing needed before differencing varies with the type of image, but is essential to ensure good subtraction of static features. This is commonly used in fields such as time-domain astronomy (known primarily as difference imaging) to find objects that fluctuate in brightness or move. In automated searches for asteroids or Kuiper belt objects, the target moves and will be in one place in one image, and in another place in a reference image made an hour or day later. Thus, image processing algorithms can make the fixed stars in the background disappear, leaving only the target. Distinct families of astronomical image subtraction techniques have emerged, operating in both image space or frequency space, with distinct trade-offs in both quality of subtraction and computational cost. These algorithms lie at the heart of almost all modern (and upcoming) transient surveys, and can enable the detection of even faint supernovae embedded in bright galaxies. Nevertheless, in astronomical imaging, significant 'residuals' remain around bright, complex sources, necessitating further algorithmic steps to identify candidates (known as real-bogus classification) The Hutchinson metric can be used to "measure of the discrepancy between two images for use in fractal image processing".

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  G.9972

  G.9972 (also known as G.cx) is a Recommendation developed by ITU-T that specifies a coexistence mechanism for networking transceivers capable of operating over electrical power line wiring. It allows G.hn devices to coexist with other devices implementing G.9972 and operating on the same power line wiring. G.9972 received consent during the meeting of ITU-T Study Group 15, on October 9, 2009, and final approval on June 11, 2010. G.9972 specifies two mechanisms for coexistence between G.hn home networks and broadband over power lines (BPL) Internet access networks: Frequency-division multiplexing (FDM), in which the available spectrum is divided into two parts: frequencies below 10 or 14 MHz (specific value can be selected by the access network) are reserved for the access network, while frequencies above them are reserved for the in-home network. Time-division multiplexing (TDM), in which the available channel time is split equally between both networks. 50% of time slots are allocated for the access network, and 50% are allocated to the in-home network.

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  Online Safety Amendment (Social Media Minimum Age) Act 2024

  The Online Safety Amendment (Social Media Minimum Age) Act 2024 is an Australian act of parliament that prohibits minors under the age of 16 from holding an account on certain social media platforms. It is an amendment to the Online Safety Act 2021 and was passed by the Parliament of Australia on 29 November 2024. It imposes monetary penalties on social media companies that fail to take reasonable steps to prevent minors under 16 that are located in Australia from having accounts on their services. The legislation allows the government to determine which social media platforms must ban age‑restricted users and proclaim a date for the commencement of the ban, with those provisions taking effect on 10 December 2025. Facebook, Instagram, Reddit, Snapchat, TikTok, Twitter, Threads, Twitch, Kick, and YouTube were age‑restricted on 10 December 2025, with the possibility that more platforms may be added. The act is being challenged in the High Court by the Digital Freedom Project. == Background == The ban on access to social media by young people by the federal government originated in November 2023, when shadow communications minister David Coleman introduced a private member's bill requiring the government to conduct a trial for age-verification technology on pornography and social media platforms. While the bill did not succeed, the Albanese government funded the trial in the 2024 Australian federal budget. In June 2024, opposition leader Peter Dutton pledged that a Coalition government would implement a ban on social media for under-16s within 100 days of taking office. The following month, prime minister Anthony Albanese announced the government would introduce legislation banning under-16s from social media. The Online Safety Amendment (Social Media Minimum Age) Bill 2024 was introduced into parliament by minister for communications Michelle Rowland on 21 November 2024, passing both houses on 28 November 2024. The ban on access to social media by young people by the federal government also gained momentum following an entreaty by the wife of the premier of South Australia, Peter Malinauskas, to her husband. She requested that he read The Anxious Generation by Jonathan Haidt and take action to address the impact of social media on the mental health of children. The couple have four young children, and, thinking of them, the premier thought that government should play a part in helping parents to regulate use of social media by their children at home. Malinauskas contacted former High Court chief justice Robert French, who agreed to look at the issue, and in September 2024 handed the premier a 267 page proposal, which he dubbed a "Swiss Army knife" rather than a machete, to adjust to social media's "changing landscape and its complexity". The leaders of other states and territories gave their support to Malinauskas's idea, and he took the French report to National Cabinet to collaborate with chief ministers, premiers, and the prime minister. Community support swelled after stories of parents who had lost their children to suicide after being bullied on social media were published. Albanese himself was moved by a personal letter received from Kelly O'Brien, whose 12-year-old daughter Charlotte had taken her own life due to bullying at school. An event took place at the sidelines of the United Nations General Assembly session in September 2025 at which a mother spoke of her daughter's suicide as "death by bullying ... enabled by social media". The speech won support from world leaders in Greece, Fiji, Tonga and the president of the European Commission Ursula von der Leyen. In early September 2024, South Australia proposed legislation similar to the federal law now in place. The state-based version was intended to ban users under the age of 14, unlike the federal law, which bans those under 16. The state-based law also proposed to require parental consent for 14 and 15‑year‑olds. Later in September, prime minister Anthony Albanese announced that his government intended to introduce legislation to set a minimum age requirement for social media. In November 2024, the federal government indicated their intention to engage the Age Check Certification Scheme following a tender process for an age assurance technology trial. The Albanese government's proposed ban was supported by the governments of every state and territory. Albanese described social media as a "scourge", and said "I want people to spend more time on the footy field or the netball court than they're spending on their phones", that family members are "worried sick about the safety of our kids online", and that social media "is having a negative impact on young people's mental health and on anxiety". Albanese's statements followed an earlier pledge by Liberal opposition leader Peter Dutton who was pushed by the early advocacy of shadow communications minister David Coleman to implement a ban on social media for under 16s within 100 days of being elected. The opposition organised an open letter signed by 140 experts who specialise in child welfare and technology. The opposition was concerned about the invasion of privacy that will occur with the introduction of identification-based age checks. An advocacy group for digital companies in Australia called the plans a "20th Century response to 21st Century challenges". A director of a mental health service voiced concerns, stating that "73% of young people across Australia who accessed mental health support did so through social media". == Implementation == Social media companies will receive a transition period of one year after the legislation is enacted to introduce reasonable controls preventing minors under the age of 16 from holding accounts on their services while physically located in Australia. Enforcement will involve fines of up to A$49.5 million for companies failing to take such steps, with no consequences for parents and children who violate the restrictions. There are no parental consent exceptions to the ban, and while the use of virtual private networks (VPNs) to access these services remains legal in Australia, the services are expected to try to stop under 16s from using VPNs to pretend to be outside Australia. The expectation is to make best-efforts to implement the ban on platforms including Facebook, Instagram, Reddit, Snapchat, TikTok, Twitter, Threads, Twitch, Kick and YouTube. Some social media companies are now obligated to become good enough at profiling Australian children under 16 to satisfy the Australian government they tried to implement the ban to avoid being fined. Consequently, social media companies said they will try to identify restricted users using various methods including behavioural inferencing. On 5 November 2025, it was announced that online gaming platform Roblox will not be banned, but Reddit and live-streaming platform Kick will be added to the list of platforms to be banned. A report by Age Check Certification Scheme, a UK company recruited by the government to consult on the technology used to implement the restrictions, was issued in June 2025, ahead of the December deadline to implement the ban. In June 2025, the preliminary report was released, which stated that "there are no significant technological barriers" to implementing the ban. In late July 2025, Google warned that it would sue the Australian government if YouTube was included in the ban. On 30 July, the government announced that it would extend its social media age limit to include YouTube, following advice from Grant. On 30 July 2025, the minister for communications, Anika Wells, published the Online Safety (Age-Restricted Social Media Platforms) Rules 2025, which specify exactly which types of social media platforms will be banned for certain users. On 31 August 2025, the full report was released, which stated that it would technically be possible to implement the ban; however, coordination among different services is required to successfully implement it. It also highlighted the benefits and flaws of different methods of age verification. On 16 September 2025, it was announced that the eSafety Commissioner will be able to take legal action against social media companies that have not pursued reasonable steps to bar users under the age of 16, and that fines can range up to A$49.5 million against these companies in court. On 19 November 2025, Meta announced that from 4 December their platforms (Instagram, Facebook, and Threads) would be removing users under the age of 16 ahead of the 10 December deadline. Users will be able to scan a face or provide an identity document to prove their age. On 21 November 2025, the eSafety Commissioner announced that the live-streaming platform Twitch will be included in the ban, but that Pinterest would not be. In December 2025, eSafety Commissioner Julie Inman Grant suggested efforts to block users include use by social media companies of various "signals" to identify children that are

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  Verifiable secret sharing

  In cryptography, a secret sharing scheme is verifiable if auxiliary information is included that allows players to verify their shares as consistent. More formally, verifiable secret sharing ensures that even if the dealer is malicious there is a well-defined secret that the players can later reconstruct. (In standard secret sharing, the dealer is assumed to be honest.) The concept of verifiable secret sharing (VSS) was first introduced in 1985 by Benny Chor, Shafi Goldwasser, Silvio Micali and Baruch Awerbuch. In a VSS protocol a distinguished player who wants to share the secret is referred to as the dealer. The protocol consists of two phases: a sharing phase and a reconstruction phase. Sharing: Initially the dealer holds secret as input and each player holds an independent random input. The sharing phase may consist of several rounds. At each round each player can privately send messages to other players and can also broadcast a message. Each message sent or broadcast by a player is determined by its input, its random input and messages received from other players in previous rounds. Reconstruction: In this phase each player provides its entire view from the sharing phase and a reconstruction function is applied and is taken as the protocol's output. An alternative definition given by Oded Goldreich defines VSS as a secure multi-party protocol for computing the randomized functionality corresponding to some (non-verifiable) secret sharing scheme. This definition is stronger than that of the other definitions and is very convenient to use in the context of general secure multi-party computation. Verifiable secret sharing is important for secure multiparty computation. Multiparty computation is typically accomplished by making secret shares of the inputs, and manipulating the shares to compute some function. To handle "active" adversaries (that is, adversaries that corrupt nodes and then make them deviate from the protocol), the secret sharing scheme needs to be verifiable to prevent the deviating nodes from throwing off the protocol. == Feldman's scheme == A commonly used example of a simple VSS scheme is the protocol by Paul Feldman, which is based on Shamir's secret sharing scheme combined with any encryption scheme which satisfies a specific homomorphic property (that is not necessarily satisfied by all homomorphic encryption schemes). The following description gives the general idea, but is not secure as written. (Note, in particular, that the published value gs leaks information about the dealer's secret s.) First, a cyclic group G of prime order q, along with a generator g of G, is chosen publicly as a system parameter. The group G must be chosen such that computing discrete logarithms is hard in this group. (Typically, one takes an order-q subgroup of (Z/pZ)×, where q is a prime dividing p − 1.) The dealer then computes (and keeps secret) a random polynomial P of degree t with coefficients in Zq, such that P(0) = s, where s is the secret. Each of the n share holders will receive a value P(1), ..., P(n) modulo q. Any t + 1 share holders can recover the secret s by using polynomial interpolation modulo q, but any set of at most t share holders cannot. (In fact, at this point any set of at most t share holders has no information about s.) So far, this is exactly Shamir's scheme. To make these shares verifiable, the dealer distributes commitments to the coefficients of P modulo q. If P(x) = s + a1x + ... + atxt, then the commitments that must be given are: c0 = gs, c1 = ga1, ... ct = gat. Once these are given, any party can verify their share. For instance, to verify that v = P(i) modulo q, party i can check that g v = c 0 c 1 i c 2 i 2 ⋯ c t i t = ∏ j = 0 t c j i j = ∏ j = 0 t g a j i j = g ∑ j = 0 t a j i j = g P ( i ) {\displaystyle g^{v}=c_{0}c_{1}^{i}c_{2}^{i^{2}}\cdots c_{t}^{i^{t}}=\prod _{j=0}^{t}c_{j}^{i^{j}}=\prod _{j=0}^{t}g^{a_{j}i^{j}}=g^{\sum _{j=0}^{t}a_{j}i^{j}}=g^{P(i)}} . This scheme is, at best, secure against computationally bounded adversaries, namely the intractability of computing discrete logarithms. Pedersen proposed later a scheme where no information about the secret is revealed even with a dealer with unlimited computing power. == Baghery's hash-based scheme == A recent line of research has proposed a unified framework, for building practical VSS schemes that do not necessarily require homomorphic commitments —a key requirement in traditional constructions such as Feldman's and Pedersen's schemes. The framework allows instantiations with different commitment schemes, including post-quantum secure options such as hash-based commitments. This offers a flexible and efficient approach to build VSS schemes, in which the verifiability of shares is decoupled from the need for homomorphic commitments, which are often tied to assumptions like the Discrete Logarithm (DL) problem, known to be insecure against quantum adversaries. One instantiation of the new framework uses hash-based commitments and a random oracle to construct a hash-based VSS scheme based on Shamir's secret sharing. === Protocol Overview === Sharing Phase: Given a secure hash-based commitment scheme C {\displaystyle {\mathcal {C}}} and a hash function H {\displaystyle {\mathcal {H}}} (modeled as a random oracle), to share a secret value s {\displaystyle s} among n {\displaystyle n} parties with threshold t {\displaystyle t} , the dealer acts as follows: Following Shamir sharing, the dealer samples a random degree- t {\displaystyle t} polynomial P ( X ) {\displaystyle P(X)} over a filed or ring, with P ( 0 ) = s {\displaystyle P(0)=s} . Each of the n {\displaystyle n} parties will receive a value v i = P ( i ) {\displaystyle v_{i}=P(i)} modulo q {\displaystyle q} as a share. To prove the validity of the shares, the dealer acts as follows: Samples another random degree- t {\displaystyle t} polynomial R ( X ) {\displaystyle R(X)} and n {\displaystyle n} random values γ 1 , … , γ n {\displaystyle \gamma _{1},\dots ,\gamma _{n}} from the same filed or ring. Computes a set of commitments c i = C ( P ( i ) , R ( i ) , γ i ) {\displaystyle c_{i}={\mathcal {C}}(P(i),R(i),\gamma _{i})} for i = 1 , 2 , … , n {\displaystyle i=1,2,\dots ,n} . Note that, the additional randomness γ i {\displaystyle \gamma _{i}} is used when the secret s {\displaystyle s} does not have sufficient entropy, but it can be omitted when sharing a uniformly random secret. Each of the n {\displaystyle n} parties will also receive a value γ i {\displaystyle \gamma _{i}} modulo q {\displaystyle q} as a share. Calculates a challenge value d {\displaystyle d} via a hash function d = H ( c 1 , … , c n ) {\displaystyle d={\mathcal {H}}(c_{1},\dots ,c_{n})} and then computes a polynomial Z ( X ) = R ( X ) + d ⋅ P ( X ) {\displaystyle Z(X)=R(X)+d\cdot P(X)} . Broadcasts the commitments c 1 , … , c n {\displaystyle c_{1},\dots ,c_{n}} along with Z ( X ) {\displaystyle Z(X)} as the proof and privately sends ( v i , γ i ) {\displaystyle (v_{i},\gamma _{i})} as the individual share to party i {\displaystyle i} . Verification Phase: Given an individual share ( v i , γ i ) {\displaystyle (v_{i},\gamma _{i})} and a proof ( c 1 , … , c n , Z ( X ) ) {\displaystyle (c_{1},\dots ,c_{n},Z(X))} , party i {\displaystyle i} verifies the correctness of it as below: Checks that Z ( X ) {\displaystyle Z(X)} is a valid (up to) degree- t {\displaystyle t} polynomial. Recomputes the challenge value d = H ( c 1 , … , c n ) {\displaystyle d={\mathcal {H}}(c_{1},\dots ,c_{n})} , and verifies the commitment equation c i = C ( v i , Z ( i ) − d v i , γ i ) {\displaystyle c_{i}={\mathcal {C}}(v_{i},Z(i)-dv_{i},\gamma _{i})} . If the verification fails, similar to Feldman’s and Pedersen’s schemes, the party raises a complaint. If too many complaints (more than t {\displaystyle t} ) are raised, the dealer is disqualified. In case of a complaint, the dealer can publicly reveal the disputed share to allow global verification. Honest parties can then collectively agree to either continue or disqualify the dealer. This scheme supports the sharing of both low-entropy and high-entropy secrets. Moreover, since it relies solely on secure hash functions for commitments and on a (quantum) random oracle, it plausibly achieves security even against quantum adversaries. Additionally, by using only lightweight cryptographic primitives, the scheme is considerably more efficient in practice compared to traditional VSS constructions based on number-theoretic assumptions. == Benaloh's scheme == Once n shares are distributed to their holders, each holder should be able to verify that all shares are collectively t-consistent (i.e., any subset t of n shares will yield the same, correct, polynomial without exposing the secret). In Shamir's secret sharing scheme the shares s 1 , s 2 , . . . , s n {\displaystyle s_{1},s_{2},...,s_{n}} are t-consistent if and only if the interpolation of the points ( 1 , s 1 ) , ( 2 , s 2 ) , . . . , (

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  Lose It!

  Lose It! is an American health and wellness mobile app developed by FitNow, Inc. The app generates calorie budgets for users by tracking weight, exercise, food and calorie intake, and personal goals, primarily to assist them in achieving weight loss. == History == Lose It! was developed in Boston and debuted in 2008. The app and its associated company were founded by J.J. Allaire, Charles Teague and Paul Dicristina. Prior to founding Lose It!, Teague and Allaire had founded the online research tool Onfolio, which was acquired by Microsoft in 2006. The Lose It! app was originally released as an iOS app before being released as a website in 2010 and an Android app in 2011. In 2015, Lose It! announced plans to release the app internationally. Lose It! was also available as an app for Apple Watch at its launch in 2015. The app’s “Snap It” feature, which allows users to approximate calorie counts by taking pictures of their daily meals and snacks, was released in beta in 2016. Snap It was named an Innovation Awards Honoree at the 2017 Consumer Electronics Show in Las Vegas. In 2020, Patrick Wetherille, one of the company’s earliest employees, was appointed chief executive officer. == App == Lose It! is weight loss app. The app allows users to set goals such as increasing strength, overall health/maintenance, and weight loss. It provides users recommended calorie budgets based on data such as their current weight and their desired weight. Lose It! also tracks data such as exercise/activity level and food consumption and allows users to track calories consumed by scanning barcodes for food products then retrieving calorie information for products. The app can also estimate the amount of calories in a food products. Lose It! has integration features connecting it to other apps such as Fitbit and Runkeeper. It also has social features such as joining groups and sharing progress with friends. The Premium version of the app allows users to track foods according to specific diets like keto, heart healthy or Mediterranean.

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  CANaerospace

  CANaerospace is a higher layer protocol based on Controller Area Network (CAN) which has been developed by Stock Flight Systems in 1998 for aeronautical applications. == Background == CANaerospace supports airborne systems employing the Line-replaceable unit (LRU) concept to share data across CAN and ensures interoperability between CAN LRUs by defining CAN physical layer characteristics, network layers, communication mechanisms, data types and aeronautical axis systems. CANaerospace is an open source project, was initiated to standardize the interface between CAN LRUs on the system level. CANaerospace is continuously being developed further and has also been published by NASA as the Advanced General Aviation Transport Experiments Databus Standard in 2001. It found widespread use in aeronautical research worldwide. A major research aircraft that employs several CANaerospace networks for real-time computer interconnection is the Stratospheric Observatory for Infrared Astronomy (SOFIA), a Boeing 747SP with a 2.5m astronomic telescope. CANaerospace is also frequently used in flight simulation and connects entire aircraft cockpits (i.e. in Eurofighter Typhoon simulators) to the simulation host computers. In Italy CANaerospace is used as UAV data bus technology. Furthermore, CANaerospace serves as communication network in several general aviation avionics systems. The CANaerospace interface definition closes the gap between the ISO/OSI layer 1 and 2 CAN protocol (which is implemented in the CAN controller itself) and the specific requirements of distributed systems in aircraft. It may be used as a primary or ancillary avionics network and was designed to meet the following requirements: Democratic network: CANaerospace does not require any master/slave relationships between LRUs or a "bus controller", thereby avoiding a potential single source of failure. Every node in the network has the same rights for participation in the bus traffic. Self-identifying message format: Each CANaerospace message contains information about the type of the data and the transmitting node. This allows the data to be unambiguously recognized at each receiving node. Continuous Message Numbering: Each CANaerospace message contains a continuously incremented number which allows coherent processing of messages in the receiving stations. Message Status Code: Each CANaerospace message contains information about the integrity of the data is conveying. This allows receiving stations to evaluate the quality of the received data and to react accordingly. Emergency Event Signaling: CANaerospace defines a mechanism that allows each node to transmit information about exception or error situations. This information can be used by other stations to determine the network health. Node Service Interface: As an enhancement to CAN, CANaerospace provides a means for individual stations on the network to communicate with each other using connection-oriented and connectionless services. Predefined CAN Identifier Assignment: CANaerospace offers a predefined identifier assignment list for normal operation data. In addition to the predefined list, user-defined identifier assignment lists may be used. Ease of Implementation: The amount of code to implement CANaerospace is very little by design in order to minimize the effort for testing and certification of flight safety critical systems. Openness to Extensions: All CANaerospace definitions are extendable to provide flexibility for future enhancements and to allow adaptions to the requirements of specific applications. Free Availability: No cost whatsoever apply for the use of CANaerospace. The specification can be downloaded from the Internet == Physical interface == To ensure interoperability and reliable communication, CANaerospace specifies the electrical characteristics, bus transceiver requirements and data rates with the corresponding tolerances based on ISO 11898. The bit timing calculation (baud rate accuracy, sample point definition) and robustness to electromagnetic interference are given special emphasis. Also addressed are CAN connector, wiring considerations and design guidelines to maximize electromagnetic compatibility. == Communication layers == The Bosch CAN specification itself allows messages being transmitted both periodically and aperiodically but does not cover issues like data representation, node addressing or connection-oriented protocols. CAN is entirely based on Anyone-to-Many (ATM) communication which means that CAN messages are always received by all stations in the network. The advantage of the CAN concept is inherent data consistency between all stations, the drawback is that it does not allow node addressing which is the basis for Peer-to-Peer (PTP) communication. Using CAN networks in aeronautical applications, however, demands a standard targeted to the specific requirements of airborne systems which implies that communication between individual stations in the network must be possible to enable the required degree of system monitoring. Consequently, CANaerospace defines additional ISO/OSI layer 3, 4 and 6 functions to support node addressing and unified ATM/PTP communication mechanisms. PTP communication allows to set up client/server interactions between individual stations in the network either temporarily or permanently. More than one of these interactions may be in effect at any given time and each node may be client for one operation and server for another at the same time. This CANaerospace mechanism is called "Node Service Concept" and allows i.e. to distribute system functions over several stations in the network or to control dynamic system reconfiguration in case of failure. The Node Service concept supports both connection-oriented and connectionless interactions like with TCP/IP and UDP/IP for Ethernet. Enabling both ATM and PTP communication for CAN requires the introduction of independent network layers to isolate the different types of communication. This is realized for CANaerospace by forming CAN identifier groups as shown in Figure 1. The resulting structure creates Logical Communication Channels (LCCs) and assigns a specific communication type (ATM, PTP) to each of the LCCs. User-defined LCCs provide the necessary freedom for designers and allow the implementation of CANaerospace according to the needs of specific applications. Figure 1: Logical Communication Channels for CANaerospace As a side effect, the CAN identifier groups in Figure 1 affect the priority of the message transmission in case of bus arbitration. The communication channels are therefore arranged according to their relative importance: Emergency Event Data Channel (EED): This communication channel is used for messages which require immediate action (i.e. system degradation or reconfiguration) and have to be transmitted with very high priority. Emergency Event Data uses ATM communication exclusively. High/Low Priority Node Service Data Channel (NSH/NSL): These communication channels are used for client/server interactions using PTP communication. The corresponding services may be of the connection-oriented as well as the connectionless type. NSH/NSL may also be used to support test and maintenance functions. Normal Operation Data Channel (NOD): This communication channel is used for the transmission of the data which is generated during normal system operation and described in the CANaerospace identifier assignment list. These messages may be transmitted periodically or aperiodically as well as synchronously or asynchronously. All messages which cannot be assigned to other communication channels shall use this channel. High/Low Priority User-Defined Data Channel (UDH/UDL): This channel is dedicated to communication which cannot, due to their specific characteristics, be assigned other channels without violating the CANaerospace specification. As long as the defined identifier range is used, the message content and the communication type (ATM, PTP) for these channels may be specified by the system designer. To ensure interoperability it is highly recommended that the use of these channels is minimized. Debug Service Data Channel (DSD): This channel is dedicated to messages which are used temporarily for development and test purposes only and are not transmitted during normal operation. As long as the defined identifier range is used, the message content and the communication type (ATM, PTP) for these channels may be specified by the system designer. == Data representation == The majority of the real-time control systems used in aeronautics employ "big endian" processor architectures. This data representation was therefore specified for CANaerospace as well. With big endian data representation, the most significant bit of any datum is arranged leftmost and transmitted first on CANaerospace as shown in Figure 2. Figure 2: "Big Endian" Data Representation for CANaerospace CANaerospace uses a self-identifying message

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  TikTokification

  TikTokification (also written TikTok-ification) is a term used to describe the widespread adoption of TikTok's short-form, vertical video format and its algorithmic content-delivery model across the broader social media landscape. The phenomenon encompasses the strategic and cultural changes made by competing platforms such as Instagram, YouTube, Facebook, Snapchat, and LinkedIn in response to TikTok's global dominance. Beyond platform design, the term is also used more broadly to describe shifts in media consumption habits, advertising strategies, and, more critically, the potential cognitive and psychological effects associated with constant short-form video consumption. == Background == === Origins of short-form video === The short-form video format predates TikTok. Vine, launched in 2013, popularised six-second looping videos before shutting down in 2017. TikTok itself, known as Douyin in the Chinese market, was created by the Chinese technology company ByteDance in September 2016. Following its international expansion and its 2018 merger with Musical.ly, TikTok grew rapidly. By 2020, the application had surpassed two billion total downloads worldwide, with over 800 million monthly active users. A key driver of TikTok's success was its recommendation algorithm. The platform's "For You Page" (FYP) serves content to users based on behaviour rather than follower count, making it possible for unknown creators to achieve widespread reach organically. Analysts noted that TikTok serves "fast, visually engaging, and authentic videos that feel more like entertainment than advertising," fundamentally reshaping consumer expectations of digital content. TikTok has been described as "the center of the internet for young people," where users go for entertainment, news, trends, and shopping. As of the mid-2020s, TikTok had approximately 1.12 billion monthly active users. == Platform responses == TikTok's success compelled nearly every major social media platform to restructure its product around short-form video. In 2020, Instagram launched Reels and YouTube launched Shorts, both directly in response to TikTok's growth. Platforms like Meta's Instagram Reels and Google's YouTube Shorts subsequently expanded aggressively, launching new features, creator tools, and even considering separate standalone applications to compete. LinkedIn, traditionally a professional networking site, began experimenting with TikTok-style short-form vertical video feeds. Facebook launched a singular unified video feed combining Reels, long videos, and live videos, similar in structure to TikTok's feed. Snapchat redesigned its application to combine Stories and Spotlight into a unified entertainment feed. YouTube extended its Shorts format to allow videos up to three minutes in length, up from the previous limit of sixty seconds, as of October 2024. Despite these adaptations, experts noted that none of TikTok's rivals had matched its algorithmic precision as of mid-2025. == Societal and cultural impact == === Media and journalism === News organisations have also been affected by TikTokification. Short-form video grew rapidly as a format for news content, driven in large part by TikTok's popularity. According to Pew Research Center, 17% of adults in the United States reported regularly getting news from TikTok in 2024, with 63% of teenagers saying they used the platform as a news source. In response, major publishers began creating bespoke short-form content for TikTok's audience, with organisations such as the BBC building dedicated internal TikTok teams. === Advertising and commerce === TikTokification has had significant effects on the advertising industry. US social video advertising spending was projected to surpass linear television advertising spending for the first time in 2025. Global social commerce sales were projected to reach approximately $900 billion in 2025, with platforms like Douyin and TikTok driving a large share of that growth. TikTok itself generated an estimated $23.6 billion in advertising revenue in 2024. Short-form video has been described as bridging the gap between brand awareness and direct conversion. Surveys have found that consumers trust user-generated content 8.7 times more than influencer content and 6.6 times more than branded content, prompting brands to favour creator-led video formats. === Attention spans and cognitive effects === A growing body of research has examined the cognitive consequences of heavy short-form video consumption, a set of effects sometimes referred to as "TikTok Brain." A large systematic review and meta-analysis published in Psychological Bulletin, analysing data from 98,299 participants across 71 studies, found that the more short-form video content a person watches, the poorer their cognitive performance in attention and inhibitory control. The review also found that greater engagement with short-form video was associated with higher levels of anxiety, depression, and stress, as well as sleep disturbances. The platform's inherent demand for engaging content has resulted in the proliferation of sludge content, a genre of split screen video with the main video on the top and an unrelated attention-grabbing video on the bottom, typically repetitive gameplay (notably of the endless runner mobile game Subway Surfers) or oddly satisfying videos, designed to maximize viewer retention in cases where the main video may appear uninteresting and would normally cause the viewer to skip it. Sludge content is often described as overstimulating, reflecting and contributing to declining attention spans, though the scholarly evidence supporting such claims is not conclusive. Dr. Yann Poncin, associate professor at the Child Study Center at Yale University, noted that "infinite scrolling and short-form video are designed to capture your attention in short bursts," contrasting this with earlier entertainment formats that guided audiences through longer narratives. Research suggests that children and teenagers may be particularly vulnerable, with early exposure to rapid frame changes potentially conditioning the brain's neural pathways to require constant stimulation, making it more challenging to engage with slower-paced activities. A separate study published in Nature Communications by researchers at the Technical University of Denmark documented a notable decrease in collective attention span over time, attributing it in part to the increasing volume and pace of content production and consumption online. Researchers caution, however, that the majority of relevant studies are cross-sectional, meaning they capture data at a single point in time and cannot establish causality. It remains possible that individuals with pre-existing conditions such as anxiety or attention deficits may be more likely to engage heavily with these platforms as a coping mechanism. === Academic and sociological analysis === Scholars have framed TikTokification within the context of the attention economy. A 2024 academic analysis described TikTok as representing "a new paradigm of social media communication" shaped by youth culture, mobile technology, and the economics of attention, in which spectators become active contributors to a shared content pipeline. The same analysis noted that TikTok "reflects a new mode of communication influenced by avant-garde cinema, the use of mobile technology, and the social habits of particular social groups." US social media users were projected to spend 61.1% of their time on social networks watching videos in 2025, up from 33.3% in 2019, before TikTok became widely popular, underscoring the scale of the behavioural shift. == Monetisation challenges == Despite high engagement levels, monetising short-form video has remained difficult for platforms and creators alike. Unlike long-form YouTube content, short clips offer limited space for advertisers to insert advertisements. YouTube Shorts pays approximately four cents per 1,000 views, considerably less than its long-form counterpart. From 2025 onward, platforms began introducing creator funds, advertisements, and AI-driven content recommendations as part of broader efforts to make short-form video economically sustainable for creators.

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