We study a generalization of the k -median problem with respect to an arbitrary dissimilarity measure D. Given a finite set P of size n , our goal is to find a set C of size k such that the sum of errors D( P,C ) = ∑ p ∈ P min c ∈ C {D( p,c )} is minimized. The main result in this article can be stated as follows: There exists a (1+ϵ)-approximation algorithm for the k -median problem with respect to D, if the 1-median problem can be approximated within a factor of (1+ϵ) by taking a random sample of constant size and solving the 1-median problem on the sample exactly. This algorithm requires time n 2 O ( mk log( mk /ϵ)), where m is a constant that depends only on ϵ and D. Using this characterization, we obtain the first linear time (1+ϵ)-approximation algorithms for the k -median problem in an arbitrary metric space with bounded doubling dimension, for the Kullback-Leibler divergence (relative entropy), for the Itakura-Saito divergence, for Mahalanobis distances, and for some special cases of Bregman divergences. Moreover, we obtain previously known results for the Euclidean k -median problem and the Euclidean k -means problem in a simplified manner. Our results are based on a new analysis of an algorithm of Kumar et al. [2004].
Abstract.A general method to secure cryptographic algorithms against side-channel attacks is the use of randomization techniques and, in particular, masking. Roughly speaking, using random values unknown to an adversary one masks the input to a cryptographic algorithm. As a result, the intermediate results in the algorithm computation are uncorrelated to the input and the adversary cannot obtain any useful information from the side-channel. Unfortunately, previous AES randomization techniques have based their security on heuristics and experiments. Thus, flaws have been found which make AES randomized implementations still vulnerable to side-channel cryptanalysis. In this paper, we provide a formal notion of security for randomized maskings of arbitrary cryptographic algorithms. Furthermore, we present an AES randomization technique that is provably secure against side-channel attacks if the adversary is able to access a single intermediate result. Our randomized masking technique is quite general and it can be applied to arbitrary algorithms using only arithmetic operations over some finite field. To our knowledge this is the first time that a randomization technique for the AES has been proven secure in a formal model.
We introduce a novel approach for sending messages over lossy packet-based networks. The new method, called Priority Encoding Transmission, allows a user to specify a different priority on each segment of the message. Based on the priorities, the sender uses the system to encode the segments into packets for transmission. The system ensures recovery of the segments in order of their priority. The priority of a segment determines the minimum number of packets sufficient to recover the segment.We define a measure for a set of priorities, called the rate, which dictates how much information about the message must be contained in each bit of the encoding. We develop systems for implementing any set of priorities with rate equal to one. We also give an information-theoretic proof that there is no system that implements a set of priorities with rate greater than one. This work has applications to multi-media and high speed networks applications, especially in those with bursty sources and multiple receivers with heterogeneous capabilities.
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