Channel Capacity for Adversaries With Computationally Bounded Observations

IEEE TRANSACTIONS ON INFORMATION THEORY(2024)

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摘要
We study reliable communication over point-to-point adversarial channels in which the adversary can observe the transmitted codeword via some function that takes the n-bit codeword as input and computes an rn-bit output for some given r is an element of [0,1]. We consider the scenario where the rn-bit observation is computationally bounded- the adversary is free to choose an arbitrary observation function as long as the function can be computed using a polynomial amount of computational resources. This observation-based restriction differs from conventional channel-based computational limitations, where in the later case, the resource limitation applies to the computation of the (adversarial) channel error/corruption. For all r is an element of [0,1 - H(p)] where H() is the binary entropy function and p is the adversary's error budget, we characterize the capacity of the above channel and find that the capacity is identical to the completely oblivious setting (r = 0). This result can be viewed as a generalization of known results on myopic adversaries and on channels with active eavesdroppers for which the observation process depends on a fixed distribution and fixed-linear structure, respectively, that cannot be chosen arbitrarily by the adversary.
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关键词
Computational modeling,Decoding,Codes,Channel models,Channel capacity,Stochastic processes,Integrated circuit modeling,Adversarial channels,capacity,arbitrarily varying channels
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