Download PDF by K. T. Arasu, J. F. Dillon (auth.), A. Pott, P. V. Kumar, T.: Difference Sets, Sequences and their Correlation Properties

By K. T. Arasu, J. F. Dillon (auth.), A. Pott, P. V. Kumar, T. Helleseth, D. Jungnickel (eds.)

ISBN-10: 0792359593

ISBN-13: 9780792359593

ISBN-10: 9401144591

ISBN-13: 9789401144599

The clarification of the formal duality of Kerdock and Preparata codes is without doubt one of the impressive ends up in the sector of utilized algebra within the previous few years. This result's regarding the invention of enormous units of quad­ riphase sequences over Z4 whose correlation homes are higher than these of the easiest binary sequences. additionally, the correlation homes of sequences are heavily on the topic of distinction houses of definite units in (cyclic) teams. it's the goal of this e-book to demonstrate the relationship among those 3 subject matters. so much articles grew out of lectures given on the NATO advert­ vanced examine Institute on "Difference units, sequences and their correlation properties". This workshop happened in undesirable Windsheim (Germany) in August 1998. The editors thank the NATO clinical Affairs department for the beneficiant aid of this workshop. with no this help, the current number of articles shouldn't have been realized.

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Extra info for Difference Sets, Sequences and their Correlation Properties

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As the components of computer circuits become very small, their description must be given by quantum mechanics. Over time there developed a curiosity about the power of quantum computation, until Shor (1994) found a way of exploiting quantum superposition to provide a polynomial time algorithm for factoring integers. This was the first example of an important problem that a quantum computer could solve more efficiently than a classical computer. The design of quantum algorithms for different classes of problems, for instance finding short vectors in lattices, is currently an active area of research.

These keystreams (k t ) make attacks based on the Berlekamp-Massey shift register synthesis algorithm, which is described in Berlekamp (1968) and Massey (1969), difficult if not infeasible. Indeed, the results of Key (1976) and Rueppel and Staffelbach (1987) show that if the s ~FSRs have primitive feedback polynomials of relatively prime degrees rl, ... ,rs then the output sequence (k t ) has period n:=l (2Ti - 1) and linear complexity 1*(rl,"" rs) where 1* is a function related to f (in particular, the degree of 1* is large when f has high order of non-linearity - we discuss non-linear order in Section 4).

The number of non-trivial initial states for an LFSR of length Ti is 2ri - 1. Hence there are Ri(2 ri - 1) different possibilities for the part of the secret key specifying the linear feedback shift register LFSRi in the combination generator. The total number of possible keys for the system described here is II ~(2ri 8 K = 1), i=l which for suitably chosen values of Ti and s would make an exhaustive search for the right key computationally infeasible. The statistical model to be described below allows a cryptanalyst to recover the LFSRi part of the key independently of the other s - 1 LFSRs using approximately ~2ri tests, under a known plaintext (equivalently, a known keystream) attack.

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Difference Sets, Sequences and their Correlation Properties by K. T. Arasu, J. F. Dillon (auth.), A. Pott, P. V. Kumar, T. Helleseth, D. Jungnickel (eds.)

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