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Intrusionresilience via the BoundedStorage Model
 In Theory of Cryptography Conference, volume 3876 of LNCS
, 2006
"... Abstract. We introduce a new method of achieving intrusionresilience in the cryptographic protocols. More precisely we show how to preserve security of such protocols, even if a malicious program (e.g. a virus) was installed on a computer of an honest user (and it was later removed). The security o ..."
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Cited by 43 (4 self)
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, namely: sessionkey generation and entity authentication. Our method is based on the results from the BoundedStorage Model. 1
On Generating the Initial Key in the BoundedStorage Model
 In Advances in Cryptology — EUROCRYPT 2004
, 2004
"... Abstract. In the boundedstorage model (BSM) for informationtheoretically secure encryption and keyagreement one uses a random string R whose length t is greater than the assumed bound s on the adversary Eve’s storage capacity. The legitimate parties Alice and Bob share a short initial secret key ..."
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Cited by 23 (4 self)
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Abstract. In the boundedstorage model (BSM) for informationtheoretically secure encryption and keyagreement one uses a random string R whose length t is greater than the assumed bound s on the adversary Eve’s storage capacity. The legitimate parties Alice and Bob share a short initial secret key
Tight Security Proofs for the BoundedStorage Model
 In Proceedings of the 34th Annual ACM Symposium on Theory of Computing
, 2002
"... In the boundedstorage model for informationtheoretically secure encryption and keyagreement one can prove the security of a cipher based on the sole assumption that the adversary's storage capacity is bounded, say by s bits, even if her computational power is unlimited. Assume that a random ..."
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Cited by 23 (3 self)
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In the boundedstorage model for informationtheoretically secure encryption and keyagreement one can prove the security of a cipher based on the sole assumption that the adversary's storage capacity is bounded, say by s bits, even if her computational power is unlimited. Assume that a random
The boundedstorage model in the presence of a quantum adversary
 IEEE Transactions on Information Theory
, 2008
"... Abstract—An extractor is a function that is used to extract randomness. Given an imperfect random sourceX and a uniform seedY, the output (X; Y) is close to uniform. We study properties of such functions in the presence of prior quantum information about X, with a particular focus on cryptographic a ..."
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Cited by 15 (1 self)
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applications. We prove that certain extractors are suitable for key expansion in the boundedstorage model where the adversary has a limited amount of quantum memory. For extractors with onebit output we show that the extracted bit is essentially equally secure as in the case where the adversary has classical
Noninteractive Timestamping in the BoundedStorage Model
, 2009
"... A timestamping scheme is noninteractive if a stamper can stamp a document without communicating with any other player. The only communication done is at validation time. NonInteractive timestamping has many advantages, such as information theoretic privacy and enhanced robustness. NonInteractive ..."
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.e., if the adversary has bounded storage, and a long random string is broadcast to all players. To the best of our knowledge, this is the first example of a cryptographic task that is possible in the boundedstorage model but is impossible in the “standard cryptographic setting, ” even when assuming “standard
Cilk: An Efficient Multithreaded Runtime System
 JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING
, 1995
"... Cilk (pronounced "silk") is a Cbased runtime system for multithreaded parallel programming. In this paper, we document the efficiency of the Cilk workstealing scheduler, both empirically and analytically. We show that on real and synthetic applications, the "work" and "cri ..."
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Cited by 750 (40 self)
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strict" (wellstructured) programs, the Cilk scheduler achieves space, time, and communication bounds all within a constant factor of optimal. The Cilk
Efficient Variants of the ICP Algorithm
 INTERNATIONAL CONFERENCE ON 3D DIGITAL IMAGING AND MODELING
, 2001
"... The ICP (Iterative Closest Point) algorithm is widely used for geometric alignment of threedimensional models when an initial estimate of the relative pose is known. Many variants of ICP have been proposed, affecting all phases of the algorithm from the selection and matching of points to the minim ..."
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Cited by 702 (5 self)
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The ICP (Iterative Closest Point) algorithm is widely used for geometric alignment of threedimensional models when an initial estimate of the relative pose is known. Many variants of ICP have been proposed, affecting all phases of the algorithm from the selection and matching of points
Near Optimal Signal Recovery From Random Projections: Universal Encoding Strategies?
, 2004
"... Suppose we are given a vector f in RN. How many linear measurements do we need to make about f to be able to recover f to within precision ɛ in the Euclidean (ℓ2) metric? Or more exactly, suppose we are interested in a class F of such objects— discrete digital signals, images, etc; how many linear m ..."
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Cited by 1513 (20 self)
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law), then it is possible to reconstruct f to within very high accuracy from a small number of random measurements. typical result is as follows: we rearrange the entries of f (or its coefficients in a fixed basis) in decreasing order of magnitude f  (1) ≥ f  (2) ≥... ≥ f  (N), and define the weakℓp ball
Inducing Features of Random Fields
 IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
, 1997
"... We present a technique for constructing random fields from a set of training samples. The learning paradigm builds increasingly complex fields by allowing potential functions, or features, that are supported by increasingly large subgraphs. Each feature has a weight that is trained by minimizing the ..."
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Cited by 664 (14 self)
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the KullbackLeibler divergence between the model and the empirical distribution of the training data. A greedy algorithm determines how features are incrementally added to the field and an iterative scaling algorithm is used to estimate the optimal values of the weights. The random field models and techniques
Implementing data cubes efficiently
 In SIGMOD
, 1996
"... Decision support applications involve complex queries on very large databases. Since response times should be small, query optimization is critical. Users typically view the data as multidimensional data cubes. Each cell of the data cube is a view consisting of an aggregation of interest, like total ..."
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Cited by 545 (1 self)
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to materialize. The greedy algorithm performs within a small constant factor of optimal under a variety of models. We then consider the most common case of the hypercube lattice and examine the choice of materialized views for hypercubes in detail, giving some good tradeoffs between the space used
Results 1  10
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