2,068 research outputs found

    Complexity transitions in global algorithms for sparse linear systems over finite fields

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    We study the computational complexity of a very basic problem, namely that of finding solutions to a very large set of random linear equations in a finite Galois Field modulo q. Using tools from statistical mechanics we are able to identify phase transitions in the structure of the solution space and to connect them to changes in performance of a global algorithm, namely Gaussian elimination. Crossing phase boundaries produces a dramatic increase in memory and CPU requirements necessary to the algorithms. In turn, this causes the saturation of the upper bounds for the running time. We illustrate the results on the specific problem of integer factorization, which is of central interest for deciphering messages encrypted with the RSA cryptosystem.Comment: 23 pages, 8 figure

    Analysis of Parallel Montgomery Multiplication in CUDA

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    For a given level of security, elliptic curve cryptography (ECC) offers improved efficiency over classic public key implementations. Point multiplication is the most common operation in ECC and, consequently, any significant improvement in perfor- mance will likely require accelerating point multiplication. In ECC, the Montgomery algorithm is widely used for point multiplication. The primary purpose of this project is to implement and analyze a parallel implementation of the Montgomery algorithm as it is used in ECC. Specifically, the performance of CPU-based Montgomery multiplication and a GPU-based implementation in CUDA are compared

    ESTABLISHED WAYS TO ATTACK EVEN THE BEST ENCRYPTION ALGORITHM

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    Which solution is the best – public key or private key encryption? This question cannot have a very rigorous, logical and definitive answer, so that the matter be forever settled :). The question supposes that the two methods could be compared on completely the same indicators – well, from my point of view, the comparison is not very relevant. Encryption specialists have demonstrated that the sizes of public key encrypted messages are much bigger than the encrypted message using private key algorithms. From this point of view, we can say that private key algorithms are more efficient than their newer counterparts. Looking at the issue through the eyeglass of the security level, the public key encryption have a great advantage of the private key variants, their level of protection, in the most pessimistic scenarios, being at least 35 time higher. As a general rule, each type of algorithm has managed to find its own market niche where could be applicable as a best solution and be more efficient than the other encryption model.Encryption, decryption, key, cryptanalysis, brute-force, linear, differential, algebra

    Factoring Safe Semiprimes with a Single Quantum Query

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    Shor's factoring algorithm (SFA), by its ability to efficiently factor large numbers, has the potential to undermine contemporary encryption. At its heart is a process called order finding, which quantum mechanics lets us perform efficiently. SFA thus consists of a \emph{quantum order finding algorithm} (QOFA), bookended by classical routines which, given the order, return the factors. But, with probability up to 1/21/2, these classical routines fail, and QOFA must be rerun. We modify these routines using elementary results in number theory, improving the likelihood that they return the factors. The resulting quantum factoring algorithm is better than SFA at factoring safe semiprimes, an important class of numbers used in cryptography. With just one call to QOFA, our algorithm almost always factors safe semiprimes. As well as a speed-up, improving efficiency gives our algorithm other, practical advantages: unlike SFA, it does not need a randomly picked input, making it simpler to construct in the lab; and in the (unlikely) case of failure, the same circuit can be rerun, without modification. We consider generalizing this result to other cases, although we do not find a simple extension, and conclude that SFA is still the best algorithm for general numbers (non safe semiprimes, in other words). Even so, we present some simple number theoretic tricks for improving SFA in this case.Comment: v2 : Typo correction and rewriting for improved clarity v3 : Slight expansion, for improved clarit
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