• The final report does not change from the intermediate one.

We study the secrecy capacity in the vicinity of colluding eavesdroppers. Contrary to the perfect collusion assumption in previous works, our new information-theoretic model considers constraints in collusion. We derive the achievable secure rates (lower bounds on the perfect secrecy capacity), both for the discrete memoryless and Gaussian channels. We also compare the proposed rates to the non...

A new applicable wiretap channel with separated side information is considered here which consist of a sender, a legitimate receiver and a wiretapper. In the considered scenario, the links from the transmitter to the legitimate receiver and the eavesdropper experience different conditions or channel states. So, the legitimate receiver and the wiretapper listen to the transmitted signal through ...

Abstract We study a novel multi-terminal source coding setup motivated by the biclustering problem. Two separate encoders observe two i.i.d. sequences $X^n$ and $Y^n$, respectively. The goal is to find rate-limited encodings $f(x^n)$ $g(z^n)$ that maximize mutual information $\textrm{I}(\,{f(X^n)};{g(Y^n)})/n$. discuss connections of this problem with hypothesis testing against independence, pa...

In this paper, we study the information-theoretic limits of learning the structure of Bayesian networks (BNs), on discrete as well as continuous random variables, from a finite number of samples. We show that the minimum number of samples required by any procedure to recover the correct structure grows as Ω (m) and Ω (k logm+ k/m) for non-sparse and sparse BNs respectively, where m is the numbe...