Analysis and design of stream ciphers
Analysis and design of stream ciphers
Shift Register Sequences
Computation of the k-Error Linear Complexity of Binary Sequences with Period 2n
ASIAN '96 Proceedings of the Second Asian Computing Science Conference on Concurrency and Parallelism, Programming, Networking, and Security
A New Keystream Generator MUGI
FSE '02 Revised Papers from the 9th International Workshop on Fast Software Encryption
Improving the Higher Order Differential Attack and Cryptanalysis of the KN Cipher
ISW '97 Proceedings of the First International Workshop on Information Security
Higher order correlation attacks, XL algorithm and cryptanalysis of Toyocrypt
ICISC'02 Proceedings of the 5th international conference on Information security and cryptology
INDOCRYPT'05 Proceedings of the 6th international conference on Cryptology in India
A relationship between linear complexity and k-error linear complexity
IEEE Transactions on Information Theory
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We focus on the relationship between the linearization method and linear complexity and show that the linearization method is another effective technique for calculating linear complexity. We analyze its effectiveness by comparing with the logic circuit method. We compare the relevant conditions and necessary computational cost with those of the Berlekamp-Massey algorithm and the Games-Chan algorithm. The significant property of a linearization method is that it needs no output sequence from a pseudo-random number generator (PRNG) because it calculates linear complexity using the algebraic expression of its algorithm. When a PRNG has n [bit] stages (registers or internal states), the necessary computational cost is smaller than O(2n). On the other hand, the Berlekamp-Massey algorithm needs O(N2) where N ( 2n) denotes period. Since existing methods calculate using the output sequence, an initial value of PRNG influences a resultant value of linear complexity. Therefore, a linear complexity is generally given as an estimate value. On the other hand, a linearization method calculates from an algorithm of PRNG, it can determine the lower bound of linear complexity.