Digital fingerprinting is a technique for identifying users who might try to use multimedia content for unintended purposes, such as redistribution. These fingerprints are typically embedded into the content using watermarking techniques that are designed to be robust to a variety of attacks. A cost-e#ective attack against such digital fingerprints is collusion, where several di#erently marked copies of the same content are combined to disrupt the underlying fingerprints. In this paper, we investigate the problem of designing fingerprints that can withstand collusion and allow for the identification of colluders. We begin by introducing the collusion problem for additive embedding. We then study the e#ect that averaging collusion has upon orthogonal modulation. We introduce an e#cient detection algorithm for identifying the fingerprints associated with K colluders that requires log(n/K)) correlations for a group of n users. We next develop a fingerprinting scheme based upon code modulation that does not require as many basis signals as orthogonal modulation. We propose a new class of codes, called anti-collusion codes (ACC), which have the property that the composition of any subset of K or fewer codevectors is unique. Using this property, we can therefore identify groups of K or fewer colluders. We present a construction of binary-valued ACC under the logical AND operation that uses the theory of combinatorial designs and is suitable for both the on-o# keying and antipodal form of binary code modulation. In order to accommodate n users, our code construction requires only # n) orthogonal signals for a given number of colluders. We introduce four di#erent detection strategies that can be used with our ACC for identifying a suspect set of colluders. We demonstrate th...

Searching for a goal is a central and extensively studied problem in computer science. In classical searching problems, the cost of a search function is simply the number of queries made to an oracle that knows the position of the goal. In many robotics problems, as well as in problems from other areas, we want to charge a cost proportional to the distance between queries (e.g., the time required to travel between two query points). With this cost function in mind, the abstract problem known as the w-lane cow-path problem was designed. There are known optimal deterministic algorithms for the cow-path problem, and we give the first randomized algorithm in this paper. We show that our algorithm is optimal for two paths (w = 2), and give evidence that it is optimal for larger values of w. Subsequent to the preliminary of version of this paper, Kao, Ma, Sipser, and Yin [10] have shown that our algorithm is indeed optimal for all w 2. Our randomized algorithm gives expected performance tha...

We investigate the design of algorithms resilient to memory faults, i.e., algorithms that, despite the corruption of some memory values during their execution, are able to produce a correct output on the set of uncorrupted values. In this framework, we consider two fundamental problems: sorting and searching. In particular, we prove that any O(n log n) comparison-based sorting algorithm can tolerate at most O((n log n) ) memory faults. Furthermore, we present one comparison-based sorting algorithm with optimal space and running time that is resilient to O((n log n) ) faults. We also prove polylogarithmic lower and upper bounds on faulttolerant searching.

We investigate the problem of reliable computation in the presence of faults that may arbitrarily corrupt memory locations. In this framework, we consider the problems of sorting and searching in optimal time while tolerating the largest possible number of memory faults. In particular, we design an O(n log n) time sorting algorithm that can optimally tolerate up to O ( √ n log n) memory faults. In the special case of integer sorting, we present an algorithm with linear expected running time that can tolerate O ( √ n) faults. We also present a randomized searching algorithm that can optimally tolerate up to O(log n) memory faults in O(log n) expected time, and an almost optimal deterministic searching algorithm that can tolerate O((log n) 1−ǫ) faults, for any small positive constant ǫ, in O(log n) worst-case time. All these results improve over previous bounds.

We investigate the problem of computing in a reliable fashion in the presence of faults that may arbitrarily corrupt memory locations. In this framework, we focus on the design of resilient data structures, i.e., data structures that, despite the corruption of some memory values during their lifetime, are nevertheless able to operate correctly (at least) on the set of uncorrupted values. In particular, we present resilient search trees which achieve optimal time and space bounds while tolerating up to O ( √ log n) memory faults, where n is the current number of items in the search tree. In more detail, our resilient search trees are able to insert, delete and search for a key in O(log n + δ 2) amortized time, where δ is an upper bound on the total number of faults. The space required is O(n + δ).

Abstract. We present a family of adaptive pairwise tournaments that are provably robust against large error fractions when used to determine the largest element in a set. The tournaments use nk pairwise comparisons but have only O(k + log n) depth, where n is the number of players and k is the robustness parameter (for reasonable values of n and k). These tournaments also give a reduction from multiclass to binary classification in machine learning, yielding the best known analysis for the problem. 1

We investigate the problem of computing in the presence of faults that may arbitrarily (i.e., adversarially) corrupt memory locations. In the faulty memory model, any memory cell can get corrupted at any time, and corrupted cells cannot be distinguished from uncorrupted ones. An upper bound δ on the number of corruptions and O(1) reliable memory cells are provided. In this model, we focus on the design of resilient dictionaries, i.e., dictionaries which are able to operate correctly (at least) on the set of uncorrupted keys. We first present a simple resilient dynamic search tree, based on random sampling, with O(log n+δ) expected amortized cost per operation, and O(n) space complexity. We then propose an optimal deterministic static dictionary supporting searches in Θ(log n+δ) time in the worst case, and we show how to use it in a dynamic setting in order to support updates in O(log n + δ) amortized time. Our dynamic dictionary also supports range queries in O(log n+δ+t) worst case time, where t is the size of the output. Finally, we show that every resilient search tree (with some reasonable properties) must take Ω(log n + δ) worst-case time per search.

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Some of today’s applications run on computer platforms with large and inexpensive memories, which are also error-prone. Unfortunately, the appearance of even very few memory faults may jeopardize the correctness of the computational results. An algorithm is resilient to memory faults if, despite the corruption of some memory values before or during its execution, it is nevertheless able to get a correct output at least on the set of uncorrupted values. In this paper we will survey some recent work on reliable computation in the presence of memory faults.

We consider broadcasting with a linearly bounded number of transmission failures. For a constant parameter 0 ! ff ! 1 we assume that at most ffi faulty transmissions can occur during the first i time units of the communication process, for every natural number i. Every informed node can transmit information to at most one neighbor in a unit of time. Faulty transmissions have no effect. We investigate worst-case optimal broadcasting time under this fault model, for several communication networks. We show, for example, that for the n-node line network this time is linear in n, if ff ! 1 2 , and exponential otherwise. For the hypercube and the complete graph, broadcasting in the linearly bounded fault model can be performed in time logarithmic in the number of nodes. y Instytut Informatyki, Uniwersytet Warszawski, Banacha 2, 02-097 Warszawa, Poland. This work was done during the author's stay at the Universit'e du Qu'ebec `a Hull as a postdoctoral fellow. z D'epartement d'Informatiqu...