WS-Security Policy is a web services specification, created by IBM and 12 co-authors, that has become an OASIS standard as of version 1.2. It extends the fundamental security protocols specified by the WS-Security, WS-Trust and WS-Secure Conversation by offering mechanisms to represent the capabilities and requirements of web services as policies. Security policy assertions are based on the WS-Policy framework. Policy assertions can be used to require more generic security attributes like transport layer security
Color moments
Color moments are measures that characterise color distribution in an image in the same way that central moments uniquely describe a probability distribution. Color moments are mainly used for color indexing purposes as features in image retrieval applications in order to compare how similar two images are based on color. Usually one image is compared to a database of digital images with pre-computed features in order to find and retrieve a similar Image. Each comparison between images results in a similarity score, and the lower this score is the more identical the two images are supposed to be. == Overview == Color moments are scaling and rotation invariant. It is usually the case that only the first three color moments are used as features in image retrieval applications as most of the color distribution information is contained in the low-order moments. Since color moments encode both shape and color information they are a good feature to use under changing lighting conditions, but they cannot handle occlusion very successfully. Color moments can be computed for any color model. Three color moments are computed per channel (e.g. 9 moments if the color model is RGB and 12 moments if the color model is CMYK). Computing color moments is done in the same way as computing moments of a probability distribution. === Mean === The first color moment can be interpreted as the average color in the image, and it can be calculated by using the following formula E i = ∑ j = 1 N 1 N p i j {\displaystyle E_{i}=\textstyle \sum _{j=1}^{N}{\frac {1}{N}}p_{ij}} where N is the number of pixels in the image and p i j {\displaystyle p_{ij}} is the value of the j-th pixel of the image at the i-th color channel. === Standard Deviation === The second color moment is the standard deviation, which is obtained by taking the square root of the variance of the color distribution. σ i = ( 1 N ∑ j = 1 N ( p i j − E i ) 2 ) {\displaystyle \sigma _{i}={\sqrt {({\frac {1}{N}}\textstyle \sum _{j=1}^{N}(p_{ij}-E_{i})^{2})}}} where E i {\displaystyle E_{i}} is the mean value, or first color moment, for the i-th color channel of the image. === Skewness === The third color moment is the skewness. It measures how asymmetric the color distribution is, and thus it gives information about the shape of the color distribution. Skewness can be computed with the following formula: s i = ( 1 N ∑ j = 1 N ( p i j − E i ) 3 ) 3 σ i {\displaystyle s_{i}={\frac {\sqrt[{3}]{\left({\frac {1}{N}}\textstyle \sum _{j=1}^{N}(p_{ij}-E_{i})^{3}\right)}}{\sigma _{i}}}} === Kurtosis === Kurtosis is the fourth color moment, and, similarly to skewness, it provides information about the shape of the color distribution. More specifically, kurtosis is a measure of how extreme the tails are in comparison to the normal distribution. === Higher-order color moments === Higher-order color moments are usually not part of the color moments feature set in image retrieval tasks as they require more data in order to obtain a good estimate of their value, and also the lower-order moments generally provide enough information. == Applications == Color moments have significant applications in image retrieval. They can be used in order to compare how similar two images are. This is a relatively new approach to color indexing. The greatest advantage of using color moments comes from the fact that there is no need to store the complete color distribution. This greatly speeds up image retrieval since there are less features to compare. In addition, the first three color moments have the same units, which allows for comparison between them. === Color indexing === Color indexing is the main application of color moments. Images can be indexed, and the index will contain the computed color moments. Then, if someone has a particular image and wants to find similar images in the database, the color moments of the image of interest will also be computed. After that the following function will be used in order to compute a similarity score between the image of interest and all the images in the database: d m o m ( H , I ) = ∑ i = 1 r w i 1 | E i 1 − E i 2 | + w i 2 | σ i 1 − σ i 2 | + w i 3 | s i 1 − s i 2 | {\displaystyle d_{mom}(H,I)=\textstyle \sum _{i=1}^{r}w_{i1}|E_{i}^{1}-E_{i}^{2}|+w_{i2}|\sigma _{i}^{1}-\sigma _{i}^{2}|+w_{i3}|s_{i}^{1}-s_{i}^{2}|} where: H and I are the color distributions of the two images that are being compared i is the channel index and r is the total number of channels E i 1 {\displaystyle E_{i}^{1}} and E i 2 {\displaystyle E_{i}^{2}} are the first order moments computed for the image distributions. σ i 1 {\displaystyle \sigma _{i}^{1}} and σ i 2 {\displaystyle \sigma _{i}^{2}} are the second order moments computed for the image distributions. s_i^1 and s_i^2 are the third order moments computed for the image distributions. w i 1 {\displaystyle w_{i1}} , w i 2 {\displaystyle w_{i2}} , and w i 3 {\displaystyle w_{i3}} are weights, specified by the user, for each of the three color moments used. Finally, the images in the database will be ranked according to the computed similarity score with the image of interest, and the database images with the lowest d m o m ( H , I ) {\displaystyle d_{mom}(H,I)} value should be retrieved. "A retrieval based on d m o m ( H , I ) {\displaystyle d_{mom}(H,I)} may produce false positives because the index contains no information about the correlation between the color channels". == Example == A simple and concise example of the use of color moments for image retrieval tasks is illustrated in. Consider having several test images in a database and a "New Image". The goal is to retrieve images from the database that are similar to the "New Image". The first three color moments are used as features. There are several steps in this computation. Image preprocessing (Optional) - The image preprocessing step of the computation process is optional. For example, in this step all images could be modified to be the same size (in terms of pixels). However, since color moments are invariant to scaling, it is not necessary to make all images the same width and height. Computing the features - Use the color moments formulae in order to compute the first three moments for each of the color channels in the image. For example, if the HSV color space is used, this means that for each of the images, 9 features in total will be computed (the first three order moments for the Hue, Saturation, and Value channels). Calculating the similarity score - After computing the color moments the weights for each of the moments in the d m o m ( H , I ) {\displaystyle d_{mom}(H,I)} function should be determined by the user. The weights have to be adjusted each time in accordance with the application or condition and quality of the images. Following that the d m o m ( H , I ) {\displaystyle d_{mom}(H,I)} function is used to calculate a similarity score for the "New Image" and each of the images in the database. Ranking and image retrieval - From the previous step the d m o m ( H , I ) {\displaystyle d_{mom}(H,I)} values were obtained. Now a comparison of these values can be made in order to decide which of the images in the database are more similar to the "New Image", and thus rank the database images accordingly. The smaller the d m o m ( H , I ) {\displaystyle d_{mom}(H,I)} value is the more similar the two color distributions are supposed to be. Finally, some of the top ranked images (the ones with the smallest d m o m ( H , I ) {\displaystyle d_{mom}(H,I)} value) from the database are retrieved.
Ciphertext expansion
In cryptography, the term ciphertext expansion refers to the length increase of a message when it is encrypted. Many modern cryptosystems cause some degree of expansion during the encryption process, for instance when the resulting ciphertext must include a message-unique Initialization Vector (IV). Probabilistic encryption schemes cause ciphertext expansion, as the set of possible ciphertexts is necessarily greater than the set of input plaintexts. Certain schemes, such as Cocks Identity Based Encryption, or the Goldwasser-Micali cryptosystem result in ciphertexts hundreds or thousands of times longer than the plaintext. Ciphertext expansion may be offset or increased by other processes which compress or expand the message, e.g., data compression or error correction coding. == Reasons why Ciphertext expansion can occur == === Probabilistic Encryption === Probabilistic encryption schemes, such as the Goldwasser-Micali cryptosystem, necessarily produce ciphertexts that are longer than the original plaintexts. This is because the set of possible ciphertexts must be larger than the set of plaintexts to achieve semantic security. === Initialization Vectors (IVs) === Many block cipher modes of operation, like Cipher Block Chaining (CBC), require the use of an Initialization Vector (IV) that is unique for each message. The IV is typically appended to the ciphertext, resulting in expansion. === Redundancy and Error Correction === Some cryptographic schemes intentionally introduce redundancy or error correction codes into the ciphertext to protect against tampering or transmission errors. This added data increases the ciphertext size. === Specific Cryptosystems === Certain cryptographic schemes, such as Cocks Identity-Based Encryption, can produce ciphertexts that are hundreds or thousands of times longer than the original plaintext. This extreme expansion is a design choice to achieve the desired security properties. Ciphertext expansion can be offset or increased by other processes that compress or expand the message, such as data compression or error correction coding. The overall impact on message size depends on the relative strengths of these competing effects.
Cryptochannel
In telecommunications, a cryptochannel is a complete system of crypto-communications between two or more holders or parties. It includes: (a) the cryptographic aids prescribed; (b) the holders thereof; (c) the indicators or other means of identification; (d) the area or areas in which effective; (e) the special purpose, if any, for which provided; and (f) pertinent notes as to distribution, usage, etc. A cryptochannel is analogous to a radio circuit.
Protecting Kids From Social Media Act
Protecting Kids on Social Media Act or HB 1891 is an American law that was introduced by William Lamberth of Sumner County, Tennessee and was signed into law by Tennessee's governor on May 2, 2024. The bill requires social media websites such as X, YouTube, TikTok, Facebook and others to verify the age of users and if those users are under 18, they must have parental consent. == Progress == The law passed the Tennessee State Legislature with little opposition: the bill had only two no votes in the House from Aftyn Behn and Vincent B. Dixie, and it had zero no votes in the Senate. == Bill summary == Every social media company must verify the age of new users after the law takes effect, and if the user had created an account before the law took effect, they must verify the age of the person attempting to access the account within 14 days. If the new user or the user who originally owned an account is under 18 years of age, they must get parental consent and the third party or social media company must not retain the data from the age verification process or obtaining parental consent. Parents who are account holders of those under 18 can view the privacy settings, set daily time restrictions, and implement breaks during which the minor cannot access the account. The law is enforced by the Attorney General of Tennessee and went into effect on January 1, 2025. == Lawsuit == On October 3, 2024, the trade association NetChoice filed a lawsuit against Tennessee Attorney General Jonathan Skrmetti in the Middle District Court of Tennessee, claiming that the law violates the First Amendment. The Judge for the case is William L. Campbell Jr. An initial case management conference was originally scheduled for December 4, 2024, however it was delayed because of the Supreme Court case United States v. Skrmetti, recommending that the conference be delayed after January 20, 2025. On February 14, 2025, Judge Eli Richardson denied NetChoice's motion for a temporary restraining order because it would disrupt the status quo of the case.
Clubhouse (app)
Clubhouse is an American social audio app for iOS and Android developed by Alpha Exploration Co. that enables users to participate in real-time, audio-only communication within virtual "rooms". Launched in March 2020 by Paul Davison and Rohan Seth, the platform is characterized by its "drop-in" nature, where users can join live discussions on a wide range of topics as either listeners or speakers. The application gained attention in early 2021, operating on an invite-only model and featuring appearances from public figures such as Elon Musk, Oprah Winfrey, and Mark Zuckerberg. During this period, Clubhouse reached a reported valuation of approximately $4 billion and contributed to the expansion of similar social audio features like Twitter Spaces and Spotify Greenroom. The app later expanded to Android in May 2021 and removed its waitlist in July 2021, opening access to the general public. == History == Clubhouse began as an invite only social media startup by Paul Davison and Rohan Seth in Fall 2019. Originally designed for podcasts with the name Talkshow, the app was rebranded as "Clubhouse" and officially released for the iOS operating system in March 2020 and as of May 2021 the Android systems as well. Clubhouse was valued at $100 million after receiving funding from notable angel investors. These investors included Ryan Hoover (Founder, Product Hunt), Balaji Srinivasan (Former CTO, Coinbase), James Beshara (Co-Founder, Tilt.com), and several venture capitalists, including a $12 million Series A investment from the venture capital firm, Andreessen Horowitz, in May 2020. The app gained popularity in the early months of the COVID-19 pandemic. It had 600,000 registered users by December 2020. In January 2021, CEO Paul Davison announced that the active weekly user base on the app consisted of approximately 2 million individuals. The company announced that it would start working on an Android version of the app. In that month, the app became widely used in Germany when German podcast hosts Philipp Klöckner and Philipp Gloeckler began an invite-chain over a Telegram group. It brought German influencers, journalists, and politicians to the platform. Clubhouse raised their Series B at a $1 billion valuation. On February 1, 2021, Clubhouse had an estimated 3.5 million downloads on a global level which grew rapidly to 8.1 million downloads by February 15. This significant growth in popularity was because celebrities such as Elon Musk and Mark Zuckerberg made appearances on the app. In the same month, Clubhouse hired an Android Software Developer. A year after the app's release, the number of weekly active users was greater than 10 million, but the user base declined 21% during three weeks from late February to early March. This decline was reportedly caused by a decrease in the number of Clubhouse users after its initial release. During its initial roll out, the app was accessible only by invitation, and invitation codes on eBay were selling at up to $400. On April 5, 2021, Clubhouse partnered with Stripe to launch its first monetizing feature called Clubhouse Payments. Although testing began with only 1,000 users, after a week, the company rolled out the functionality to another 60,000 or more users in the US. In the same month, Twitter entered in discussions to purchase Clubhouse for $4 billion. The talks ended with no acquisition. Later, the company raised their Series C round of funding at a $4 billion valuation. The app also received interest in a partnership, with the National Football League announcing a content deal that month; Twitter Spaces later poached Clubhouse's exclusive NFL deal with 20 official NFL Spaces scheduled for the 2021-22 season. Finally, On May 9, 2021, Clubhouse launched a beta version of the Android app for users in the US, and on May 21, 2021, Clubhouse became available worldwide for Android users. In July 2021, Clubhouse announced a partnership with TED to offer exclusive talks. and on July 21, 2021, the company discarded its invitation system and made the application available to all, though a wait list for registration was still applied in order to manage new traffic. As of the time of the announcement, the company stated it had 10 million users on the wait list. On September 23, 2021, the company announced a new feature named "Wave". In October 2021, Clubhouse rolled out new features called "Replays and Clips". In April 2023, the company announced it was reducing its staff by half amid a "resetting" due to post-pandemic market shifts. == Features == === Rooms === The primary feature of Clubhouse is real-time virtual "rooms" in which users can communicate with each other via audio. Rooms are divided into different categories based on levels of privacy. Moderator roles are denoted by a green star that appears next to the user's name. When a user joins a room, they are initially assigned to the role of a "listener" and cannot unmute themselves. Listeners can notify the moderators of their intent to join the stage and speak by clicking on the "raise hand" icon. Users who are invited to the stage become "speakers" and can unmute themselves. Users can exit a room by tapping the "leave quietly" button or with the help of peace sign emoji. === Houses === In August 2022, Clubhouse announced a feature called Houses, an invite-based version of the rooms. === Events === A lot of conversations in Clubhouse are of spontaneous nature. However, users can schedule conversations by creating events. While scheduling an event, users can first name the event and then set the date and time at which the conversation will begin. Users can also add co-hosts to help moderate the event. Once the event has been created, it is added to the Clubhouse "bulletin". The bulletin shows upcoming scheduled events and allows users to set notifications for events by clicking the bell icon corresponding to the event. Users can access the bulletin by clicking on the calendar icon at the top of the home page. === Clubs === At the Clubhouse, clubs are user communities that regularly discuss a common interest. Many clubs are present in Clubhouse which represents a wide array of topics. Users can find clubs by name under the search tab. A club consists of three categories of users: "Admin", "Leader", and "Member". Members can create private rooms and invite more users into the club. Leaders have all the privileges of a member. Apart from that, they are authorized to create/schedule club-branded open rooms. An admin can modify club settings, add/delete users, change user privileges and create/schedule any type of room. There are three types of clubs: "Open", "By Approval", and "Closed" for membership. Any user can join an open club by pressing the "Join The Club" button on the club profile. In case of approval, users need to apply and wait for membership by clicking the "Apply To Join" button on the club profile. The admins of the respective club are privileged to accept or reject the user's request. In a closed club, membership is limited to users selected by the club admin. All users of a club will be notified when a public room within the club is created. The club creation is restricted to active users and whoever creates the club will become the club admin. Eligible users can create a club by going to their profile, press the "+" sign present in the "Member of" section. Clubs in which a user is a member are shown on their profile page. The first club to half a million members was the Human Behavior Club founded by The Digital Doctor (Dr. Sohaib Imtiaz). === Backchannel === Backchannel is the messaging function which allows users to interact individually or within a group via text. The Backchannel feature was initially leaked on June 18, 2021, in response to the launch of Spotify Greenroom. This is notable step because, until this point, Clubhouse was voice only with no way to hyperlink or message. It was entirely dependent on Instagram and Twitter for text messaging. The feature was initially leaked in the App Store, which the company says was an accident on Twitter. A month later, after multiple failed attempts, the Clubhouse Backchannel finally launched on July 14, 2021. === Explore === The homepage of Clubhouse provides access to ongoing chat rooms, which are recommended based on the people and clubs that are followed by the user. As the users tap on the magnifying glass icon, they will be redirected to the explore page. On that page, users can search for people and clubs to follow and also find conversations categorized by topics. === Clubhouse Payments === This is the direct payment service provided by the app, which allows users to send money to content creators. It includes those users who had enabled this functionality in their profile. Money can be sent from users to the creator by clicking on their profile. Press "Send Money" then enter the amount you want to send. When a user does this for the first time, they'll be prompted to reg
Merit Network
Merit Network, Inc., is a nonprofit member-governed organization providing high-performance computer networking and related services to educational, government, health care, and nonprofit organizations, primarily in Michigan. Created in 1966, Merit operates the longest running regional computer network in the United States. == Organization == Created in 1966 as the Michigan Educational Research Information Triad by Michigan State University (MSU), the University of Michigan (U-M), and Wayne State University (WSU), Merit was created to investigate resource sharing by connecting the mainframe computers at these three Michigan public research universities. Merit's initial three node packet-switched computer network was operational in October 1972 using custom hardware based on DEC PDP-11 minicomputers and software developed by the Merit staff and the staffs at the three universities. Over the next dozen years the initial network grew as new services such as dial-in terminal support, remote job submission, remote printing, and file transfer were added; as gateways to the national and international Tymnet, Telenet, and Datapac networks were established, as support for the X.25 and TCP/IP protocols was added; as additional computers such as WSU's MVS system and the UM's electrical engineering's VAX running UNIX were attached; and as new universities became Merit members. Merit's involvement in national networking activities started in the mid-1980s with connections to the national supercomputing centers and work on the 56 kbit/s National Science Foundation Network (NSFNET), the forerunner of today's Internet. From 1987 until April 1995, Merit re-engineered and managed the NSFNET backbone service. MichNet, Merit's regional network in Michigan was attached to NSFNET and in the early 1990s Merit began extending "the Internet" throughout Michigan, offering both direct connect and dial-in services, and upgrading the statewide network from 56 kbit/s to 1.5 Mbit/s, and on to 45, 155, 622 Mbit/s, and eventually 1 and 10 Gbit/s. In 2003 Merit began its transition to a facilities based network, using fiber optic facilities that it shares with its members, that it purchases or leases under long-term agreements, or that it builds. In addition to network connectivity services, Merit offers a number of related services within Michigan and beyond, including: Internet2 connectivity, VPN, Network monitoring, Voice over IP (VOIP), Cloud storage, E-mail, Domain Name, Network Time, VMware and Zimbra software licensing, Colocation, and professional development seminars, workshops, classes, conferences, and meetings. == History == === Creating the network: 1966 to 1973 === The Michigan Educational Research Information Triad (MERIT) was formed in the fall of 1966 by Michigan State University (MSU), University of Michigan (U-M), and Wayne State University (WSU). More often known as the Merit Computer Network or simply Merit, it was created to design and implement a computer network connecting the mainframe computers at the universities. In the fall of 1969, after funding for the initial development of the network had been secured, Bertram Herzog was named director for MERIT. Eric Aupperle was hired as senior engineer, and was charged with finding hardware to make the network operational. The National Science Foundation (NSF) and the State of Michigan provided the initial funding for the network. In June 1970, the Applied Dynamics Division of Reliance Electric in Saline, Michigan was contracted to build three Communication Computers or CCs. Each would consist of a Digital Equipment Corporation (DEC) PDP-11 computer, dataphone interfaces, and interfaces that would attach them directly to the mainframe computers. The cost was to be slightly less than the $300,000 ($2,487,100, adjusted for inflation) originally budgeted. Merit staff wrote the software that ran on the CCs, while staff at each of the universities wrote the mainframe software to interface to the CCs. The first completed connection linked the IBM S/360-67 mainframe computers running the Michigan Terminal System at WSU and U-M, and was publicly demonstrated on December 14, 1971. The MSU node was completed in October 1972, adding a CDC 6500 mainframe running Scope/Hustler. The network was officially dedicated on May 15, 1973. === Expanding the network: 1974 to 1985 === In 1974, Herzog returned to teaching in the University of Michigan's Industrial Engineering Department, and Aupperle was appointed as director. Use of the all uppercase name "MERIT" was abandoned in favor of the mixed case "Merit". The first network connections were host to host interactive connections which allowed person to remote computer or local computer to remote computer interactions. To this, terminal to host connections, batch connections (remote job submission, remote printing, batch file transfer), and interactive file copy were added. And, in addition to connecting to host computers over custom hardware interfaces, the ability to connect to hosts or other networks over groups of asynchronous ports and via X.25 were added. Merit interconnected with Telenet (later SprintNet) in 1976 to give Merit users dial-in access from locations around the United States. Dial-in access within the U.S. and internationally was further expanded via Merit's interconnections to Tymnet, ADP's Autonet, and later still the IBM Global Network as well as Merit's own expanding network of dial-in sites in Michigan, New York City, and Washington, D.C. In 1978, Western Michigan University (WMU) became the fourth member of Merit (prompting a name change, as the acronym Merit no longer made sense as the group was no longer a triad). To expand the network, the Merit staff developed new hardware interfaces for the Digital PDP-11 based on printed circuit technology. The new system became known as the Primary Communications Processor (PCP), with the earliest PCPs connecting a PDP-10 located at WMU and a DEC VAX running UNIX at U-M's Electrical Engineering department. A second hardware technology initiative in 1983 produced the smaller Secondary Communication Processors (SCP) based on DEC LSI-11 processors. The first SCP was installed at the Michigan Union in Ann Arbor, creating UMnet, which extended Merit's network connectivity deeply into the U-M campus. In 1983 Merit's PCP and SCP software was enhanced to support TCP/IP and Merit interconnected with the ARPANET. === National networking, NSFNET, and the Internet: 1986 to 1995 === In 1986 Merit engineered and operated leased lines and satellite links that allowed the University of Michigan to access the supercomputing facilities at Pittsburgh, San Diego, and NCAR. In 1987, Merit, IBM and MCI submitted a winning proposal to NSF to implement a new NSFNET backbone network. The new NSFNET backbone network service began July 1, 1988. It interconnected supercomputing centers around the country at 1.5 megabits per second (T1), 24 times faster than the 56 kilobits-per-second speed of the previous network. The NSFNET backbone grew to link scientists and educators on university campuses nationwide and connect them to their counterparts around the world. The NSFNET project caused substantial growth at Merit, nearly tripling the staff and leading to the establishment of a new 24-hour Network Operations Center at the U-M Computer Center. In September 1990 in anticipation of the NSFNET T3 upgrade and the approaching end of the 5-year NSFNET cooperative agreement, Merit, IBM, and MCI formed Advanced Network and Services (ANS), a new non-profit corporation with a more broadly based Board of Directors than the Michigan-based Merit Network. Under its cooperative agreement with NSF, Merit remained ultimately responsible for the operation of NSFNET, but subcontracted much of the engineering and operations work to ANS. In 1991 the NSFNET backbone service was expanded to additional sites and upgraded to a more robust 45 Mbit/s (T3) based network. The new T3 backbone was named ANSNet and provided the physical infrastructure used by Merit to deliver the NSFNET Backbone Service. On April 30, 1995, the NSFNET project came to an end, when the NSFNET backbone service was decommissioned and replaced by a new Internet architecture with commercial Internet service providers (ISPs) interconnected at Network Access Points provided by multiple providers across the country. === Bringing the Internet to Michigan: 1985 to 2001 === During the 1980s, Merit Network grew to serve eight member universities, with Oakland University joining in 1985 and Central Michigan University, Eastern Michigan University, and Michigan Technological University joining in 1987. In 1990, Merit's board of directors formally changed the organization's name to Merit Network, Inc., and created the name MichNet to refer to Merit's statewide network. The board also approved a staff proposal to allow organizations other than publicly supported universities, referred to as aff