In wiretap model of secure communication the goal is to provide (asymptotic) perfect secrecy and reliable communication over a noisy channel that is eavesdropped by an adversary with unlimited computational power. This goal is achieved by taking advantage of the channel noise and without requiring a shared key. The model has attracted attention in recent years because it captures eavesdropping attack in wireless communication. The wiretap adversary is a passive eavesdropping adversary at the physical layer of communication. In this paper we propose a model for adversarial wiretap (AWTP) channel that models active adversaries at this layer. We consider a @math wiretap adversary who can see a fraction @math , and modify a fraction @math , of the sent codeword. The code components that are read and or modified can be chosen adaptively, and the subsets of read and modified components in general, can be different. AWTP codes provide secrecy and reliability for communication over these channels. We give security and reliability definitions and measures for these codes, and define secrecy capacity of an AWTP channel that represents the secrecy potential of the channel. The paper has two main contributions. First, we prove a tight upper bound on the rate of AWTP codes with perfect secrecy for @math -AWTP channels, and use the bound to derive the secrecy capacity of the channel. We prove a similar bound for @math -secure codes also, but in this case the bound is not tight. Second, we give an explicit construction for a capacity achieving AWTP code family, and prove its security and efficiency properties. We show that AWTP model is a natural generalization of Wyner's wiretap models and somewhat surprisingly, also provides a direct generalization for a seemingly unrelated cryptographic primitive, Secure Message Transmission (SMT).
Our adversarial channel model can be seen as a special class of arbitrarily varying channel. For this class we can remove some of the restrictions of the above line of work. More specifically, (i) we do not assume shared randomness between the sender and the receiver, (ii) we consider an integrated adaptive eavesdropping and jamming adversary and assume that to corrupt the next symbol, the adversary uses all its knowledge up to that point; (iii) we allow adversary to choose the message distribution and so the error is worst case; and finally (iv) the secrecy measure in our case is in terms of statistical distance between the adversary's views of two adversarially chosen messages. We note that in @cite_50 , secrecy is measured as the mutual information of a random message (uniform distribution on messages) and the adversary's view. Our security definition using statistical distance is equivalent to the mutual information security when the message distribution is adversarially chosen @cite_49 .
@cite_49 @cite_50
2963230393 2145385126 1964657953 2170255835
We introduce randomized Limited View (LV) adversary codes that provide protection against an adversary that uses their partial view of the channel to construct an adversarial error vector that is added to the channel. For a codeword of length N, the adversary selects a subset of size ρrN of components to “see”, and then “adds” an adversarial error vector of weight ρwN to the codeword. Performance of the code is measured by the probability of the decoder failure in recovering the sent message. An (N, qRN, δ)-limited view adversary is a code of rate R that ensures that the success chance of the adversary in making decoder to fail is bounded by δ. Our main motivation to study these codes is providing protection for wireless communication at the physical layer of networks. We formalize the definition of adversarial error and decoder failure, construct a code with efficient encoding and decoding that allows the adversary to, depending on the code rate, read up to half of the sent codeword and add error on the same coordinates. The code is non-linear, has an efficient decoding algorithm, and is constructed using a message authentication code (MAC) and a Folded Reed-Solomon (FRS) code. The decoding algorithm uses an innovative approach that combines the list decoding algorithm of the FRS codes and the MAC verification algorithm to eliminate the exponential size of the list output from the decoding algorithm. We discuss our results and future work. Consider two parties who wish to communicate in order to execute some interactive protocol π. However, the communication channel between them is noisy: An adversary sees everything that is transmitted over the channel and can change a constant fraction of the bits arbitrarily, thus interrupting the execution of π (which was designed for an error-free channel). If π only contains a single long message, then a good error correcting code would overcome the noise with only a constant overhead in communication. However, this solution is not applicable to interactive protocols consisting of many short messages. Schulman [1992, 1993] introduced the notion of interactive coding: A simulator that, given any protocol π, is able to simulate it (i.e., produce its intended transcript) even in the presence of constant rate adversarial channel errors, and with only constant (multiplicative) communication overhead. However, the running time of Schulman's simulator, and of all simulators that followed, has been exponential (or subexponential) in the communication complexity of π (which we denote by N). In this work, we present three efficient simulators, all of which are randomized and have a certain failure probability (over the choice of coins). The first runs in time poly(N), has failure probability roughly 2-N, and is resilient to 1 32-fraction of adversarial error. The second runs in time O(N log N), has failure probability roughly 2-N, and is resilient to some constant fraction of adversarial error. The third runs in time O(N), has failure probability 1 poly(N), and is resilient to some constant fraction of adversarial error. (Computational complexity is measured in the RAM model.) The first two simulators can be made deterministic if they are a priori given a random string (which may be known to the adversary ahead of time). In particular, the simulators can be made to be nonuniform and deterministic (with equivalent performance). In this paper we consider the problem of designing a medium access control (MAC) protocol for single-hop wireless networks that is provably robust against adaptive adversarial jamming. The wireless network consists of a set of honest and reliable nodes that are within the transmission range of each other. In addition to these nodes there is an adversary. The adversary may know the protocol and its entire history and use this knowledge to jam the wireless channel at will at any time. It is allowed to jam a (1-epsilon)-fraction of the time steps, for an arbitrary constant epsilon>0, but it has to make a jamming decision before it knows the actions of the nodes at the current step. The nodes cannot distinguish between the adversarial jamming or a collision of two or more messages that are sent at the same time. We demonstrate, for the first time, that there is a local-control MAC protocol requiring only very limited knowledge about the adversary and the network that achieves a constant throughput for the non-jammed time steps under any adversarial strategy above. We also show that our protocol is very energy efficient and that it can be extended to obtain a robust and efficient protocol for leader election and the fair use of the wireless channel. This paper explores what kinds of information two parties must communicate in order to correct errors which occur in a shared secret string W. Any bits they communicate must leak a significant amount of information about W --- that is, from the adversary's point of view, the entropy of W will drop significantly. Nevertheless, we construct schemes with which Alice and Bob can prevent an adversary from learning any useful information about W. Specifically, if the entropy of W is sufficiently high, then there is no function f(W) which the adversary can learn from the error-correction information with significant probability.This leads to several new results: (a) the design of noise-tolerant "perfectly one-way" hash functions in the sense of [7], which in turn leads to obfuscation of proximity queries for high entropy secrets W; (b) private fuzzy extractors [11], which allow one to extract uniformly random bits from noisy and nonuniform data W, while also insuring that no sensitive information about W is leaked; and (c) noise tolerance and stateless key re-use in the Bounded Storage Model, resolving the main open problem of Ding [10].The heart of our constructions is the design of strong randomness extractors with the property that the source W can be recovered from the extracted randomness and any string W' which is close to W.