Vanish was a project to "give users control over the lifetime of personal data stored on the web." It was led by Roxana Geambasu at the University of Washington. The project proposed to allow a user to enter information to send across the internet, thereby relinquishing control of it. However, the user can include an "expiration date," after which the information is no longer usable by anyone who may have a copy of it, even the creator. The Vanish approach was found to be vulnerable to a Sybil attack and thus insecure by a team called Unvanish from the University of Texas, University of Michigan, and Princeton. == Theory == Vanish acts by automating the encryption of information entered by the user with an encryption key that is unknown to the user. Along with the information the user enters, the user also enters metadata concerning how long the information should remain available. The system then encrypts the information but does not store either the encryption key or the original information. Instead, it breaks up the decryption key into smaller components that are disseminated across distributed hash tables, or DHTs, via the Internet. The DHTs refresh information within their nodes on a set schedule unless configured to make the information persistent. The time delay entered by the user in the metadata controls how long the DHTs should allow the information to persist, but once that time period is over, the DHTs will reuse those nodes, making the information about the decryption stored irretrievable. As long as the decryption key may be reassembled from the DHTs, the information is retrievable. However, once the period entered by the user has lapsed, the information is no longer recoverable, as the user never possessed the decryption key. == Implementation == Vanish currently exists as a Firefox plug-in which allows a user to enter text into either a standard Gmail email or Facebook message and choose to send the message via Vanish. The message is then encrypted and sent via the normal networking pathways through the cloud to the recipient. The recipient must have the same Firefox plug-in to decrypt the message. The plugin accesses BitTorrent DHTs, which have 8-hour lifespans. This means the user may select an expiration date for the message in increments of 8 hours. After the expiration of the user-defined time span, the information in the DHT is overwritten, thereby eliminating the key. While both the user and recipient may have copies of the original encrypted message, the key used to turn it back into plain text is now gone. Although this particular instance of the data has become inaccessible, it's important to note that the information can always be saved by other means before expiration (copied or even via screen shots) and published again.
Smoothing
In statistics and image processing, to smooth a data set is to create an approximating function that attempts to capture important patterns in the data, while leaving out noise or other fine-scale structures/rapid phenomena. In smoothing, the data points of a signal are modified so individual points higher than the adjacent points (presumably because of noise) are reduced, and points that are lower than the adjacent points are increased, leading to a smoother signal. Reducing noise by smoothing may aid in data analysis in two notable ways: Help uncover more meaningful information from the underlying data, such as trends. Provide analyses that are both flexible and robust. Many different algorithms are used in smoothing, most commonly binning, kernels, and local weighted regression. == Compared to curve fitting == Smoothing may be distinguished from the related and partially overlapping concept of curve fitting in the following ways: curve fitting often involves the use of an explicit function form for the result, whereas the immediate results from smoothing are the "smoothed" values with no later use made of a functional form if there is one; the aim of smoothing is to give a general idea of relatively slow changes of value with little attention paid to the close matching of data values, while curve fitting concentrates on achieving as close a match as possible. smoothing methods often have an associated tuning parameter which is used to control the extent of smoothing. Curve fitting will adjust any number of parameters of the function to obtain the 'best' fit. == Linear smoothers == In the case that the smoothed values can be written as a linear transformation of the observed values, the smoothing operation is known as a linear smoother; the matrix representing the transformation is known as a smoother matrix or hat matrix. The operation of applying such a matrix transformation is called convolution. Thus the matrix is also called convolution matrix or a convolution kernel. In the case of simple series of data points (rather than a multi-dimensional image), the convolution kernel is a one-dimensional vector. == Algorithms == One of the most common algorithms is the "moving average", often used to try to capture important trends in repeated statistical surveys. In image processing and computer vision, smoothing ideas are used in scale space representations. The simplest smoothing algorithm is the "rectangular" or "unweighted sliding-average smooth". This method replaces each point in the signal with the average of "m" adjacent points, where "m" is a positive integer called the "smooth width". Usually m is an odd number. The triangular smooth is like the rectangular smooth except that it implements a weighted smoothing function. Some specific smoothing and filter types, with their respective uses, pros and cons are:
Forking lemma
The forking lemma is any of a number of related lemmas in cryptography research. The lemma states that if an adversary (typically a probabilistic Turing machine), on inputs drawn from some distribution, produces an output that has some property with non-negligible probability, then with non-negligible probability, if the adversary is re-run on new inputs but with the same random tape, its second output will also have the property. This concept was first used by David Pointcheval and Jacques Stern in "Security proofs for signature schemes," published in the proceedings of Eurocrypt 1996. In their paper, the forking lemma is specified in terms of an adversary that attacks a digital signature scheme instantiated in the random oracle model. They show that if an adversary can forge a signature with non-negligible probability, then there is a non-negligible probability that the same adversary with the same random tape can create a second forgery in an attack with a different random oracle. The forking lemma was later generalized by Mihir Bellare and Gregory Neven. The forking lemma has been used and further generalized to prove the security of a variety of digital signature schemes and other random-oracle based cryptographic constructions. == Statement of the lemma == The generalized version of the lemma is stated as follows. Let A be a probabilistic algorithm, with inputs (x, h1, ..., hq; r) that outputs a pair (J, y), where r refers to the random tape of A (that is, the random choices A will make). Suppose further that IG is a probability distribution from which x is drawn, and that H is a set of size h from which each of the hi values are drawn according to the uniform distribution. Let acc be the probability that on inputs distributed as described, the J output by A is greater than or equal to 1. We can then define a "forking algorithm" FA that proceeds as follows, on input x: Pick a random tape r for A. Pick h1, ..., hq uniformly from H. Run A on input (x, h1, ..., hq; r) to produce (J, y). If J = 0, then return (0, 0, 0). Pick h'J, ..., h'q uniformly from H. Run A on input (x, h1, ..., hJ−1, h'J, ..., h'q; r) to produce (J', y'). If J' = J and hJ ≠ h'J then return (1, y, y'), otherwise, return (0, 0, 0). Let frk be the probability that FA outputs a triple starting with 1, given an input x chosen randomly from IG. Then frk ≥ acc ⋅ ( acc q − 1 h ) . {\displaystyle {\text{frk}}\geq {\text{acc}}\cdot \left({\frac {\text{acc}}{q}}-{\frac {1}{h}}\right).} === Intuition === The idea here is to think of A as running two times in related executions, where the process "forks" at a certain point, when some but not all of the input has been examined. In the alternate version, the remaining inputs are re-generated but are generated in the normal way. The point at which the process forks may be something we only want to decide later, possibly based on the behavior of A the first time around: this is why the lemma statement chooses the branching point (J) based on the output of A. The requirement that hJ ≠ h'J is a technical one required by many uses of the lemma. (Note that since both hJ and h'J are chosen randomly from H, then if h is large, as is usually the case, the probability of the two values not being distinct is extremely small.) === Example === For example, let A be an algorithm for breaking a digital signature scheme in the random oracle model. Then x would be the public parameters (including the public key) A is attacking, and hi would be the output of the random oracle on its ith distinct input. The forking lemma is of use when it would be possible, given two different random signatures of the same message, to solve some underlying hard problem. An adversary that forges once, however, gives rise to one that forges twice on the same message with non-negligible probability through the forking lemma. When A attempts to forge on a message m, we consider the output of A to be (J, y) where y is the forgery, and J is such that m was the Jth unique query to the random oracle (it may be assumed that A will query m at some point, if A is to be successful with non-negligible probability). (If A outputs an incorrect forgery, we consider the output to be (0, y).) By the forking lemma, the probability (frk) of obtaining two good forgeries y and y' on the same message but with different random oracle outputs (that is, with hJ ≠ h'J) is non-negligible when acc is also non-negligible. This allows us to prove that if the underlying hard problem is indeed hard, then no adversary can forge signatures. This is the essence of the proof given by Pointcheval and Stern for a modified ElGamal signature scheme against an adaptive adversary. == Known issues with application of forking lemma == The reduction provided by the forking lemma is not tight. Pointcheval and Stern proposed security arguments for Digital Signatures and Blind Signature using Forking Lemma. Claus P. Schnorr provided an attack on blind Schnorr signatures schemes, with more than p o l y l o g ( n ) {\displaystyle polylog(n)} concurrent executions (the case studied and proven secure by Pointcheval and Stern). A polynomial-time attack, for Ω ( n ) {\displaystyle \Omega (n)} concurrent executions, was shown in 2020 by Benhamouda, Lepoint, Raykova, and Orrù. Schnorr also suggested enhancements for securing blind signatures schemes based on discrete logarithm problem.
Social Media Working Group Act of 2014
The Social Media Working Group Act of 2014 (H.R. 4263) is a bill that would direct the United States Secretary of Homeland Security to establish within the United States Department of Homeland Security (DHS) a social media working group (the Group) to provide guidance and best practices to the emergency preparedness and response community on the use of social media technologies before, during, and after a terrorist attack. The bill was introduced into the United States House of Representatives during the 113th United States Congress. == Background == === Social media === Social media is the social interaction among people in which they create, share or exchange information and ideas in virtual communities and networks. Andreas Kaplan and Michael Haenlein define social media as "a group of Internet-based applications that build on the ideological and technological foundations of Web 2.0, and that allow the creation and exchange of user-generated content." Furthermore, social media depend on mobile and web-based technologies to create highly interactive platforms through which individuals and communities share, co-create, discuss, and modify user-generated content. They introduce substantial and pervasive changes to communication between organizations, communities, and individuals. Social media differ from traditional or industrial media in many ways, including quality, reach, frequency, usability, immediacy, and permanence. === Virtual Social Media Working Group === First responders have increasingly used social media in emergency response and recovery operations. Social media tools are used to connect with citizens after a disaster and share information. The Virtual Social Media Working group (VSMWG) is an online platform that gives advice to first responders on how to safely and effectively use social media in emergency response operations. The working group is made up of subject matter experts from across the U.S. It was created by DHS in December 2010 and gives first responders guidance and best practices regarding the use of social media during emergencies. The DHS S&T and the VSMWG work with local and state governments, academics and nonprofits. Meetings of the VSMWG are chaired by the Under Secretary of Homeland Security for Science and Technology. == Provisions of the bill == This summary is based largely on the summary provided by the Congressional Research Service, a public domain source. The Social Media Working Group Act of 2014 would amend the Homeland Security Act of 2002 to direct the United States Secretary of Homeland Security to establish within the United States Department of Homeland Security (DHS) a social media working group (the Group) to provide guidance and best practices to the emergency preparedness and response community on the use of social media technologies before, during, and after a terrorist attack. The bill would require the Group to submit an annual report that includes: (1) a review of current and emerging social media technologies being used to support preparedness and response activities related to terrorist attacks, of best practices and lessons learned on the use of social media during the response to terrorist attacks that occurred during the period covered by the report, and of available training for government officials on the use of social media in response to a terrorist attack; (2) recommendations to improve DHS's use of social media and to improve information sharing among DHS and its components and among state and local governments; and (3) a summary of coordination efforts with the private sector to discuss and resolve legal, operational, technical, privacy, and security concerns. == Congressional Budget Office report == This summary is based largely on the summary provided by the Congressional Budget Office, as ordered reported by the House Committee on Homeland Security on June 11, 2014. This is a public domain source. H.R. 4263 would direct the Department of Homeland Security (DHS) to establish a working group to provide guidance and best practices on the use of social media technologies, specifically during a terrorist attack or other emergency. The group would prepare guidance for the emergency preparedness and response community. The bill would define the membership of the working group, which would include more than 20 experts from federal, state, local, and tribal governments along with nongovernmental organizations. The working group would be exempt from the Federal Advisory Committee Act and would be authorized to hold virtual meetings to fulfill the requirement to meet twice a year. The working group would be required to submit an annual report on emerging trends and best practices for emergency response through social media. Based on the cost of similar activities carried out under the DHS Acquisition and Accountability Efficiency Act and the Critical Infrastructure Research and Development Advancement Act of 2013, the Congressional Budget Office (CBO) estimates that the new DHS responsibilities and the annual report required by H.R. 4263 would cost a total of less than $500,000 annually, assuming the availability of appropriated funds. Enacting the legislation would not affect direct spending or revenues; therefore, pay-as-you-go procedures do not apply. H.R. 4263 contains no intergovernmental or private-sector mandates as defined in the Unfunded Mandates Reform Act and would impose no costs on state, local, or tribal governments. == Procedural history == The Social Media Working Group Act of 2014 was introduced into the United States House of Representatives on March 14, 2014, by Rep. Susan W. Brooks (R, IN-5). It was referred to the United States House Committee on Homeland Security and the United States House Homeland Security Subcommittee on Emergency Preparedness, Response, and Communications. On June 19, 2014, it was reported (amended) alongside House Report 113-480. On July 8, 2014, the House voted in Roll Call Vote 369 to pass the bill 375–19. == Debate and discussion == Nate Elliott, a social media expert at Forrester Research, explains that "the hope is when government or another authority tweets something, people will share it for them," but that this often doesn't happen. This problem, that "messages wash away very quickly," is the reason that the federal government is trying to formulate a better social media strategy. Rep. Steven Palazzo (R-MS), who co-sponsored the bill, stated that "social media has played a crucial role in emergency preparedness and response in Mississippi, including during disasters like Hurricane Isaac and the tornadoes that hit the Hattiesburg area a little over a year ago." He said that their goal with the bill was to "build upon existing public-private partnerships and use social media in a more strategic way in order to help save lives and property."
Reverse proxy
In computer networks, a reverse proxy or surrogate server is a proxy server that appears to any client to be an ordinary web server, but in reality merely acts as an intermediary that forwards the client's requests to one or more ordinary web servers. Reverse proxies help increase scalability, performance, resilience, and security, but they also carry a number of risks. Companies that run web servers often set up reverse proxies to facilitate the communication between an Internet user's browser and the web servers. An important advantage of doing so is that the web servers can be hidden behind a firewall on a company-internal network, and only the reverse proxy needs to be directly exposed to the Internet. Reverse proxy servers are implemented in popular open-source web servers. Dedicated reverse proxy servers are used by some of the biggest websites on the Internet. A reverse proxy is capable of tracking IP addresses of requests that are relayed through it as well as reading and/or modifying any non-encrypted traffic. However, this implies that anyone who has compromised the server could do so as well. Reverse proxies differ from forward proxies, which are used when the client is restricted to a private, internal network and asks a forward proxy to retrieve resources from the public Internet. == Uses == Large websites and content delivery networks use reverse proxies, together with other techniques, to balance the load between internal servers. Reverse proxies can keep a cache of static content, which further reduces the load on these internal servers and the internal network. It is also common for reverse proxies to add features such as compression or TLS encryption to the communication channel between the client and the reverse proxy. Reverse proxies can inspect HTTP headers, which, for example, allows them to present a single IP address to the Internet while relaying requests to different internal servers based on the URL of the HTTP request. Reverse proxies can hide the existence and characteristics of origin servers. This can make it more difficult to determine the actual location of the origin server / website and, for instance, more challenging to initiate legal action such as takedowns or block access to the website, as the IP address of the website may not be immediately apparent. Additionally, the reverse proxy may be located in a different jurisdiction with different legal requirements, further complicating the takedown process. Application firewall features can protect against common web-based attacks, like a denial-of-service attack (DoS) or distributed denial-of-service attacks (DDoS). Without a reverse proxy, removing malware or initiating takedowns (while simultaneously dealing with the attack) on one's own site, for example, can be difficult. In the case of secure websites, a web server may not perform TLS encryption itself, but instead offload the task to a reverse proxy that may be equipped with TLS acceleration hardware. (See TLS termination proxy.) A reverse proxy can distribute the load from incoming requests to several servers, with each server supporting its own application area. In the case of reverse proxying web servers, the reverse proxy may have to rewrite the URL in each incoming request in order to match the relevant internal location of the requested resource. A reverse proxy can reduce load on its origin servers by caching static content and dynamic content, known as web acceleration. Proxy caches of this sort can often satisfy a considerable number of website requests, greatly reducing the load on the origin server(s). A reverse proxy can optimize content by compressing it in order to speed up loading times. In a technique named "spoon-feeding", a dynamically generated page can be produced in its entirety and served to the reverse proxy, which can feed the page to the client as the connection allows. The program that generates the page need not remain open, thus releasing server resources during the possibly extended time the client requires to complete the transfer. Reverse proxies can operate wherever multiple web-servers must be accessible via a single public IP address. The web servers listen on different ports in the same machine, with the same local IP address or, possibly, on different machines with different local IP addresses. The reverse proxy analyzes each incoming request and delivers it to the right server within the local area network. Reverse proxies can perform A/B testing and multivariate testing without requiring application code to handle the logic of which version is served to a client. A reverse proxy can add access authentication to a web server that does not have any authentication. == Risks == When the transit traffic is encrypted and the reverse proxy needs to filter/cache/compress or otherwise modify or improve the traffic, the proxy first must decrypt and re-encrypt communications. This requires the proxy to possess the TLS certificate and its corresponding private key, extending the number of systems that can have access to non-encrypted data and making it a more valuable target for attackers. The vast majority of external data breaches happen either when hackers succeed in abusing an existing reverse proxy that was intentionally deployed by an organization, or when hackers succeed in converting an existing Internet-facing server into a reverse proxy server. Compromised or converted systems allow external attackers to specify where they want their attacks proxied to, enabling their access to internal networks and systems. Applications that were developed for the internal use of a company are not typically hardened to public standards and are not necessarily designed to withstand all hacking attempts. When an organization allows external access to such internal applications via a reverse proxy, they might unintentionally increase their own attack surface and invite hackers. If a reverse proxy is not configured to filter attacks or it does not receive daily updates to keep its attack signature database up to date, a zero-day vulnerability can pass through unfiltered, enabling attackers to gain control of the system(s) that are behind the reverse proxy server. Giving the reverse proxy of a third party access to private keys (for caching or optimizing content) places the entire triad of confidentiality, integrity and availability in the hands of the third party who operates the proxy. A reverse proxy is a single point of failure for the back-end services it fronts: an outage caused by misconfiguration, a denial-of-service attack, or a software fault can make every fronted service unreachable to outside clients, even when the back-end services themselves remain healthy. For example, a 2020 outage at Cloudflare briefly took down major sites and services that relied on its reverse-proxy edge, including Discord.
Connectionist expert system
Connectionist expert systems are artificial neural network (ANN) based expert systems where the ANN generates inferencing rules e.g., fuzzy-multi layer perceptron where linguistic and natural form of inputs are used. Apart from that, rough set theory may be used for encoding knowledge in the weights better and also genetic algorithms may be used to optimize the search solutions better. Symbolic reasoning methods may also be incorporated (see hybrid intelligent system). (Also see expert system, neural network, clinical decision support system.)
ServerNet
ServerNet is a switched fabric communications link primarily used in proprietary computers made by Tandem Computers, Compaq, and HP. Its features include good scalability, clean fault containment, error detection and failover. The ServerNet architecture specification defines a connection between nodes, either processor or high performance I/O nodes such as storage devices. == History == Tandem Computers developed the original ServerNet architecture and protocols for use in its own proprietary computer systems starting in 1992, and released the first ServerNet systems in 1995. Early attempts to license the technology and interface chips to other companies failed, due in part to a disconnect between the culture of selling complete hardware / software / middleware computer systems and that needed for selling and supporting chips and licensing technology. A follow-on development effort ported the Virtual Interface Architecture to ServerNet with PCI interface boards connecting personal computers. Infiniband directly inherited many ServerNet features. As of 2017, systems still ship based on the ServerNet architecture.