Coding against delayed adversaries

In this work we consider the communication of information in the presence of a delayed adversarial jammer. In the setting under study, a sender wishes to communicate a message to a receiver by transmitting a codeword x = (x<inf>1</inf>, …, x<inf>n</inf>) over a communication channel. The adversarial jammer can view the transmitted symbols xi one at a time, but must base its action (when changing x<inf>i</inf>) on x<inf>j</inf> for j ≤ i - Δ<inf>n</inf>, where Δ ∈ [0, 1] is a delay parameter. In this work, we study codes for a class of delayed adversaries, and for any delay Δ > 0 present a single letter characterization of the achievable communication rate in the presence of such adversaries.

[1]  D. Blackwell,et al.  The Capacities of Certain Channel Classes Under Random Coding , 1960 .

[2]  D. A. Bell,et al.  Information Theory and Reliable Communication , 1969 .

[3]  Imre Csiszár,et al.  Arbitrarily varying channels with constrained inputs and states , 1988, IEEE Trans. Inf. Theory.

[4]  Imre Csiszár,et al.  The capacity of the arbitrarily varying channel revisited: Positivity, constraints , 1988, IEEE Trans. Inf. Theory.

[5]  David J. C. MacKay,et al.  Information Theory, Inference, and Learning Algorithms , 2004, IEEE Transactions on Information Theory.

[6]  Silvio Micali,et al.  Optimal Error Correction Against Computationally Bounded Noise , 2005, TCC.

[7]  Kyomin Jung,et al.  On Computationally Bounded Adverserial Capacity , 2006 .

[8]  Adam D. Smith Scrambling adversarial errors using few random bits, optimal information reconciliation, and better private codes , 2007, SODA '07.

[9]  Anand D. Sarwate,et al.  Robust and adaptive communication under uncertain interference , 2008 .

[10]  Michael Langberg,et al.  Oblivious Communication Channels and Their Capacity , 2008, IEEE Transactions on Information Theory.

[11]  Devdatt P. Dubhashi,et al.  Concentration of Measure for the Analysis of Randomized Algorithms: Contents , 2009 .

[12]  Michael Langberg,et al.  Codes against online adversaries , 2008, 2009 47th Annual Allerton Conference on Communication, Control, and Computing (Allerton).

[13]  Venkatesan Guruswami,et al.  Explicit Capacity-achieving Codes for Worst-Case Additive Errors , 2009, ArXiv.

[14]  Michael Langberg,et al.  Binary causal-adversary channels , 2009, 2009 IEEE International Symposium on Information Theory.

[15]  Anand D. Sarwate,et al.  Zero-Rate Feedback Can Achieve the Empirical Capacity , 2007, IEEE Transactions on Information Theory.

[16]  Imre Csiszár,et al.  Information Theory - Coding Theorems for Discrete Memoryless Systems, Second Edition , 2011 .