On the Shannon Cipher System With a Wiretapper Guessing Subject to Distortion and Reliability Requirements

In this paper we discuss the processes in the Shannon cipher system with discrete memoryless source and a guessing wiretapper. The wiretapper observes a cryptogram of $N$-vector of ciphered messages in the public channel and tries to guess successively the vector of messages within given distortion level $\Delta$ and small probability of error less than $\exp \{-NE\}$ with positive reliability index $E$. The security of the system is measured by the expected number of guesses which wiretapper needs for the approximate reconstruction of the vector of source messages. The distortion, the reliability criteria and the possibility of upper limiting the number of guesses extend the approach studied by Merhav and Arikan. A single-letter characterization is given for the region of pairs $(R_L,R)$ (of the rate $R_L$ of the maximum number of guesses $L(N)$ and the rate $R$ of the average number of guesses) in dependence on key rate $R_K$, distortion level $\Delta$ and reliability $E$.Comment: 14 pages, 3 figures, Submitted to IEEE Transactions on Information Theor

Some Useful Integral Representations for Information-Theoretic Analyses

This work is an extension of our earlier article, where a well-known integral representation of the logarithmic function was explored, and was accompanied with demonstrations of its usefulness in obtaining compact, easily-calculable, exact formulas for quantities that involve expectations of the logarithm of a positive random variable. Here, in the same spirit, we derive an exact integral representation (in one or two dimensions) of the moment of a nonnegative random variable, or the sum of such independent random variables, where the moment order is a general positive noninteger real (also known as fractional moments). The proposed formula is applied to a variety of examples with an information-theoretic motivation, and it is shown how it facilitates their numerical evaluations. In particular, when applied to the calculation of a moment of the sum of a large number, $n$, of nonnegative random variables, it is clear that integration over one or two dimensions, as suggested by our proposed integral representation, is significantly easier than the alternative of integrating over $n$ dimensions, as needed in the direct calculation of the desired moment.Comment: Published in Entropy, vol. 22, no. 6, paper 707, pages 1-29, June 2020. Available at: https://www.mdpi.com/1099-4300/22/6/70

Tight Bounds on the R\'enyi Entropy via Majorization with Applications to Guessing and Compression

This paper provides tight bounds on the R\'enyi entropy of a function of a discrete random variable with a finite number of possible values, where the considered function is not one-to-one. To that end, a tight lower bound on the R\'enyi entropy of a discrete random variable with a finite support is derived as a function of the size of the support, and the ratio of the maximal to minimal probability masses. This work was inspired by the recently published paper by Cicalese et al., which is focused on the Shannon entropy, and it strengthens and generalizes the results of that paper to R\'enyi entropies of arbitrary positive orders. In view of these generalized bounds and the works by Arikan and Campbell, non-asymptotic bounds are derived for guessing moments and lossless data compression of discrete memoryless sources.Comment: The paper was published in the Entropy journal (special issue on Probabilistic Methods in Information Theory, Hypothesis Testing, and Coding), vol. 20, no. 12, paper no. 896, November 22, 2018. Online available at https://www.mdpi.com/1099-4300/20/12/89

Centralized vs Decentralized Multi-Agent Guesswork

We study a notion of guesswork, where multiple agents intend to launch a coordinated brute-force attack to find a single binary secret string, and each agent has access to side information generated through either a BEC or a BSC. The average number of trials required to find the secret string grows exponentially with the length of the string, and the rate of the growth is called the guesswork exponent. We compute the guesswork exponent for several multi-agent attacks. We show that a multi-agent attack reduces the guesswork exponent compared to a single agent, even when the agents do not exchange information to coordinate their attack, and try to individually guess the secret string using a predetermined scheme in a decentralized fashion. Further, we show that the guesswork exponent of two agents who do coordinate their attack is strictly smaller than that of any finite number of agents individually performing decentralized guesswork.Comment: Accepted at IEEE International Symposium on Information Theory (ISIT) 201