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Secure Function Evaluation
Secure two-party computation (2PC, or secure function evaluation) is a sub-problem of secure multi-party computation (MPC) that has received special attention by researchers because of its close relation to many cryptographic tasks. The goal of 2PC is to create a generic protocol that allows two parties to jointly compute an arbitrary function on their inputs without sharing the value of their inputs with the opposing party. One of the most well known examples of 2PC is Yao's Millionaires' problem, in which two parties, Alice and Bob, are millionaires who wish to determine who is wealthier without revealing their wealth. Formally, Alice has wealth a, Bob has wealth b, and they wish to compute a \geq b without revealing the values a or b. Yao's garbled circuit protocol for two-party computation only provided security against passive adversaries. One of the first general solutions for achieving security against active adversary was introduced by Goldreich, Micali and Wigderson by ap ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] [Amazon] |
Secure Multi-party Computation
Secure multi-party computation (also known as secure computation, multi-party computation (MPC) or privacy-preserving computation) is a subfield of cryptography with the goal of creating methods for parties to jointly compute a function over their inputs while keeping those inputs private. Unlike traditional cryptographic tasks, where cryptography assures security and integrity of communication or storage and the adversary is outside the system of participants (an eavesdropper on the sender and receiver), the cryptography in this model protects participants' privacy from each other. The foundation for secure multi-party computation started in the late 1970s with the work on mental poker, cryptographic work that simulates game playing/computational tasks over distances without requiring a trusted third party. Traditionally, cryptography was about concealing content, while this new type of computation and protocol is about concealing partial information about data while computing with ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] [Amazon] |
Trust (social Sciences)
Trust is the belief that another person will do what is expected. It brings with it a willingness for one social entity, party (the trustor) to become vulnerable to another party (the trustee), on the presumption that the trustee will act in ways that benefit the trustor. In addition, the trustor does not have control over the actions of the trustee. Scholars distinguish between generalized trust (also known as social trust), which is the extension of trust to a relatively large circle of unfamiliar others, and particularized trust, which is contingent on a specific situation or a specific relationship. As the trustor is uncertainty, uncertain about the outcome of the trustee's actions, the trustor can only develop and evaluate expectations. Such expectations are formed with a view to the motivations of the trustee, dependent on their characteristics, the situation, and their interaction. The uncertainty stems from the risk of failure or harm to the trustor if the trustee does n ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] [Amazon] |
Oblivious Transfer
In cryptography, an oblivious transfer (OT) protocol is a type of protocol in which a sender transfers one of potentially many pieces of information to a receiver, but remains oblivious as to what piece (if any) has been transferred. The first form of oblivious transfer was introduced in 1981 by Michael O. Rabin. In this form, the sender sends a message to the receiver with probability 1/2, while the sender remains oblivious as to whether or not the receiver received the message. Rabin's oblivious transfer scheme is based on the RSA cryptosystem. A more useful form of oblivious transfer called 1–2 oblivious transfer or "1 out of 2 oblivious transfer", was developed later by Shimon Even, Oded Goldreich, and Abraham Lempel, in order to build protocols for secure multiparty computation. It is generalized to "1 out of ''n'' oblivious transfer" where the user gets exactly one database element without the server getting to know which element was queried, and without the user know ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] [Amazon] |
Computationally Indistinguishable
In computational complexity and cryptography, two families of distributions are computationally indistinguishable if no efficient algorithm can tell the difference between them except with negligible probability. Formal definition Let \scriptstyle\_ and \scriptstyle\_ be two distribution ensembles indexed by a security parameter ''n'' (which usually refers to the length of the input); we say they are computationally indistinguishable if for any non-uniform probabilistic polynomial time algorithm ''A'', the following quantity is a negligible function in ''n'': : \delta(n) = \left, \Pr_ A(x) = 1- \Pr_ A(x) = 1\. denoted D_n \approx E_n. In other words, every efficient algorithm ''As behavior does not significantly change when given samples according to ''D''''n'' or ''E''''n'' in the limit as n\to \infty. Another interpretation of computational indistinguishability, is that polynomial-time algorithms actively trying to distinguish between the two ensembles cannot do so: that any ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] [Amazon] |
Statistically Close
In statistics, probability theory, and information theory, a statistical distance quantifies the distance between two statistical objects, which can be two random variables, or two probability distributions or samples, or the distance can be between an individual sample point and a population or a wider sample of points. A distance between populations can be interpreted as measuring the distance between two probability distributions and hence they are essentially measures of distances between probability measures. Where statistical distance measures relate to the differences between random variables, these may have statistical dependence, and hence these distances are not directly related to measures of distances between probability measures. Again, a measure of distance between random variables may relate to the extent of dependence between them, rather than to their individual values. Many statistical distance measures are not metrics, and some are not symmetric. Some types ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] [Amazon] |
Computationally Bounded Adversary
In information theory, the computationally bounded adversary problem is a different way of looking at the problem of sending data over a noisy channel. In previous models the best that could be done was ensuring correct decoding for up to ''d''/2 errors, where d was the Hamming distance of the code. The problem with doing it this way is that it does not take into consideration the actual amount of computing power available to the adversary. Rather, it only concerns itself with how many bits of a given code word can change and still have the message decode properly. In the computationally bounded adversary model the channel – the adversary – is restricted to only being able to perform a reasonable amount of computation to decide which bits of the code word need to change. In other words, this model does not need to consider how many errors can possibly be handled, but only how many errors could possibly be introduced given a reasonable amount of computing power on the part of the ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] [Amazon] |
Information Theory
Information theory is the mathematical study of the quantification (science), quantification, Data storage, storage, and telecommunications, communication of information. The field was established and formalized by Claude Shannon in the 1940s, though early contributions were made in the 1920s through the works of Harry Nyquist and Ralph Hartley. It is at the intersection of electronic engineering, mathematics, statistics, computer science, Neuroscience, neurobiology, physics, and electrical engineering. A key measure in information theory is information entropy, entropy. Entropy quantifies the amount of uncertainty involved in the value of a random variable or the outcome of a random process. For example, identifying the outcome of a Fair coin, fair coin flip (which has two equally likely outcomes) provides less information (lower entropy, less uncertainty) than identifying the outcome from a roll of a dice, die (which has six equally likely outcomes). Some other important measu ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] [Amazon] |
Secure Channel
In cryptography, a secure channel is a means of data transmission that is resistant to overhearing and tampering. A confidential channel is a means of data transmission that is resistant to overhearing, or eavesdropping (e.g., reading the content), but not necessarily resistant to tampering (i.e., manipulating the content). An authentic channel is a means of data transmission that is resistant to tampering but not necessarily resistant to overhearing. In contrast to a secure channel, an insecure channel is unencrypted and may be subject to eavesdropping and tampering. Secure communications are possible over an insecure channel if the content to be communicated is encrypted prior to transmission. Secure channels in the real world There are no perfectly secure channels in the real world. There are, at best, only ways to make insecure channels (e.g., couriers, homing pigeons, diplomatic bags, etc.) less insecure: padlocks (between courier wrists and a briefcase), loyalty tes ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] [Amazon] |
Cryptographic
Cryptography, or cryptology (from "hidden, secret"; and ''graphein'', "to write", or '' -logia'', "study", respectively), is the practice and study of techniques for secure communication in the presence of adversarial behavior. More generally, cryptography is about constructing and analyzing protocols that prevent third parties or the public from reading private messages. Modern cryptography exists at the intersection of the disciplines of mathematics, computer science, information security, electrical engineering, digital signal processing, physics, and others. Core concepts related to information security ( data confidentiality, data integrity, authentication, and non-repudiation) are also central to cryptography. Practical applications of cryptography include electronic commerce, chip-based payment cards, digital currencies, computer passwords, and military communications. Cryptography prior to the modern age was effectively synonymous with encryption, convert ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] [Amazon] |
Vitaly Shmatikov
Vitaly Shmatikov is a professor in computer security at Cornell Tech. Biography Shmatikov obtained his M.S. in engineering-economic systems at Stanford University, and then Ph.D. in computer science from Stanford University in 2000 under the supervision of John C. Mitchell, where he wrote his dissertation on Finite-State Analysis of Security Protocols. He currently has over 100 publications in the area of computer security, privacy, and cryptography. Research The Netflix Prize was a competition to predict how users would rate films based on their previous ratings of other films. The dataset contained data from 480,189 users who rated 17,770 movies. In 2008, with Arvind Narayanan, Shmatikov showed that it was possible to de-anonymize individual people from this dataset. To do this, Shmatikov used a second auxiliary dataset of various user's IMDb ratings. By correlating users who made similar reviews, it was possible to nearly perfectly de-identify several people who were present ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] [Amazon] |
