On Counteracting Byzantine Attacks in Network Coded Peer-to-Peer Networks

Random linear network coding can be used in peer-to-peer networks to increase the efficiency of content distribution and distributed storage. However, these systems are particularly susceptible to Byzantine attacks. We quantify the impact of Byzantine attacks on the coded system by evaluating the probability that a receiver node fails to correctly recover a file. We show that even for a small probability of attack, the system fails with overwhelming probability. We then propose a novel signature scheme that allows packet-level Byzantine detection. This scheme allows one-hop containment of the contamination, and saves bandwidth by allowing nodes to detect and drop the contaminated packets. We compare the net cost of our signature scheme with various other Byzantine schemes, and show that when the probability of Byzantine attacks is high, our scheme is the most bandwidth efficient.Comment: 26 pages, 9 figures, Submitted to IEEE Journal on Selected Areas in Communications (JSAC) "Mission Critical Networking

Groebner bases and multidimensional FIR multirate systems

The polyphase representation with respect to sampling lattices in multidimensional (M-D) multirate signal processing allows us to identify perfect reconstruction (PR) filter banks with unimodular Laurent polynomial matrices, and various problems in the design and analysis of invertible MD multirate systems can be algebraically formulated with the aid of this representation. While the resulting algebraic problems can be solved in one dimension (1-D) by the Euclidean Division Algorithm, we show that Gröbner bases offers an effective solution to them in the M-D case

Audio watermarking for monitoring and copy protection

Based on existing technology used in image and video wa-termarking, we have developed a robust audio watermark-ing technique. The embedding algorithm operates in fre-quency domain, where the magnitudes of the Fourier co-efficients are slightly modified. In the temporal domain, an additional scale parameter and gain function are neces-sary to refine the watermark and achieve perceptual trans-parency. Watermark detection relies on the Symmetrical Phase Only Matched Filtering (SPOMF) cross-correlation approach. Not only the presence of a watermark, but also its cyclic shift is detected. This shift supports a multi-bit payload for one particular watermark sequence. The water-marking technology proved to be very robust o a large num-ber of signal processing "attacks " such as MP3 (64 kb/s), all-pass filtering, echo addition, time-scale modification, re-sampling, noise addition, etc. It is expected that this ap-proach may contribute in a wide variety of existing (e.g. monitoring and copy protection) and future applications

Title: A Security Risk for Publicly Available Watermark Detectors

this paper we have addressed the issue of watermark security based on the availability of a watermark detector and a single watermarked image. We extended the work started in #5# and #1# by presenting a simple attack method. A slight extension of the theory shows that the same method is applicable to all correlation based watermark methods. This implies that watermarking methods based upon thresholded correlation are not suited for applications where the detector is publicly available #DVD

Decision Making with Side Information

decision, learning, risk, loss, convergence, identification, estimation We consider the problem of decision-making with side information and unbounded loss functions. Inspired by probably approximately correct learning model, we use a slightly different model that incorporates the notion of side information in a more generic form to make it applicable to a broader class of applications including parameter estimation and system identification. We address sufficient conditions for consistent decisionmaking with exponential convergence behavior. In this regard, besides a certain condition on the growth function of the class of loss functions, it suffices that the class of loss functions be dominated by a measurable function whose exponential Orlicz expectation is uniformly bounded over the probabilistic model. Decay exponent, decay constant, and sample complexity are discussed. Example applications to method of moments, maximum likelihood estimation, and system identification are illustrated, as well