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Information-centric networks (ICNs) replace IP addresses with content names at the thin waist of the Internet hourglass, thereby enabling pervasive router-level caching at the network layer. In this paper, we revisit pervasive content caching and propose an algorithm for cache replacement at ICN routers by incorporating principles from network coding, a technique used to achieve maximum flow rates in multicast. By introducing a low computational cost in the system, network-coded caching better utilizes the available small storage space at the routers to cache more effectively in the network. Results of our experiments on the global enterprise for network innovations (GENI) testbed demonstrating the performance of our algorithm on a real network are included in the paper. We evaluate the algorithm in two different traffic scenarios (i) video-on-demand (VoD) (ii) Zipf-based web traffic. Working with the named data networking implementation of ICN, we also present the additional headers and logical components that are needed to enable network-coded caching. In a nutshell, we show that an integrated coding-and-caching strategy can provide significant gains in latency and content delivery rate for a small computational overhead. � 2015, Springer Science+Business Media New York.

Physical layer security protocols exploit inviolable physical laws at the signal level for providing guarantees on secrecy of communications. These protocols invariably involve randomized encoding at the transmitter, for which an ideal random number generator is typically assumed in the literature. In this work, we study the impact of using weak Pseudo Random Number Generators (PRNGs) in physical layer security protocols for coding and forward key distribution over Binary Symmetric and Gaussian wiretap channels. In the case of wiretap channel coding, we study fast correlation attacks that aim to retrieve the initial seed used in the PRNGs. Our results show that randomized coset encoding, which forms an important part of wiretap channel coding, provides useful robustness against fast correlation attacks. In the case of single-round or forward key distribution over a Gaussian wiretap channel, the bits from a PRNG are nonlinearly transformed to generate Gaussian-distributed pseudo random numbers at the transmitter. In such cases, we design modified versions of the fast correlation attacks accounting for the effects of the nonlinear transformation and soft input. We observe that, even for moderately high memory, the success probability of the modified fast correlation attacks become the same as that of a random guess in many cases. � 2014 IEEE.

It was well known from Shannon's days that characteristics of the physical channel like attenuation, fading and noise can impair reliable communication. But it was more recently that the beneficial side effects of channel characteristics in ensuring secret communication started getting attention. Studies have been made to quantify the amount of secrecy that can be reaped by combining channel coding with security protocols. The Wiretap channel proposed by Wyner is arguably one of the oldest models of physical layer security protocols. In this paper, we present a brief tutorial introduction to the Wiretap channel, followed by an application of the physical layer model to a class of Key Distribution protocols. We present results from an implementation of key distribution protocols using Software Defined Radio tools along with physical RF hardware peripherals. We believe this approach is much more tangible and informative than computer based simulation studies. � 2013, DESIDOC.

We consider heterogeneous cellular networks (HetNet) where each base station (BS) sends unique training signal based on its physical layer cell identity. Received signal at mobile terminal (MT) is superposition of training signals from different BS. Neither BS identities nor their channel response is known apriori at MT. For this scenario, we consider the problem of finding constituent BS identities from superimposed components in received signal. Though number of BS with unique identities can be quite large in a HetNet, in any given scenario, actual number of BS interfering at MT is relatively few. By exploiting this sparseness, we show that our problem can be solved using block sparse signal reconstruction algorithms under compressive sensing framework where sensing matrix is block-matrix with circulant-blocks (BCB). We apply convex programming based l2l1 mixed norm minimization and greed based subspace matching pursuit approaches to recover interfering BS identities. We characterize block restricted isometry property, mutual subspace incoherence of BCB matrices with i.i.d. Rademacher distributed entries and establish certain recovery guarantees. Our proposed approaches give significant improvements over conventional successive interference cancellation approach over both randomly generated and 3GPP-LTE training signals. � 1972-2012 IEEE.