Titlebook: Complexity of Lattice Problems; A Cryptographic Pers Daniele Micciancio,Shafi Goldwasser Book 2002 Springer Science+Business Media New York

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Book 2002relatively poor quality of the solution it gives in the worst case, allowed to devise polynomial time solutions to many classical problems in computer science. These include, solving integer programs in a fixed number of variables, factoring polynomials over the rationals, breaking knapsack based cr

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0893-3405 n computer science. These include, solving integer programs in a fixed number of variables, factoring polynomials over the rationals, breaking knapsack based cr978-1-4613-5293-8978-1-4615-0897-7Series ISSN 0893-3405

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Approximation Algorithms,l time algorithms to find approximately shortest nonzero vectors in a lattice, or lattice vectors approximately closest to a given target point. The approximation factor achieved is exponential in the rank of the lattice. In Section 1 we start with an algorithm to solve SVP in dimension 2. For the s

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Shortest Vector Problem,to find the shortest nonzero vector in the lattice generated by . . In Chapter 3 we have already studied another important algorithmic problem on lattices: the closest vector problem (CVP). In CVP, in addition to the lattice basis ., one is given a target vector ., and the goal is to find the lattic

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Cryptographic Functions,n cryptography is that of secret communication: two parties want to communicate with each other, and keep the conversation private, i.e., no one, other than the two legitimate parties, should be able to get any information about the messages being exchanged. This secrecy goal can be achieved if the