Computer Science – Cryptography and Security
Scientific paper
2010-06-30
Computer Science
Cryptography and Security
5 pages
Scientific paper
The cryptanalysis of various cipher problems can be formulated as NP-Hard combinatorial problem. Solving such problems requires time and/or memory requirement which increases with the size of the problem. Techniques for solving combinatorial problems fall into two broad groups - exact algorithms and Evolutionary Computation algorithms. An exact algorithms guarantees that the optimal solution to the problem will be found. The exact algorithms like branch and bound, simplex method, brute force etc methodology is very inefficient for solving combinatorial problem because of their prohibitive complexity (time and memory requirement). The Evolutionary Computation algorithms are employed in an attempt to find an adequate solution to the problem. A Evolutionary Computation algorithm - Genetic algorithm, simulated annealing and tabu search were developed to provide a robust and efficient methodology for cryptanalysis. The aim of these techniques to find sufficient "good" solution efficiently with the characteristics of the problem, instead of the global optimum solution, and thus it also provides attractive alternative for the large scale applications. This paper focuses on the methodology of Evolutionary Computation algorithms .
No associations
LandOfFree
Evolutionary Computation Algorithms for Cryptanalysis: A Study does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Evolutionary Computation Algorithms for Cryptanalysis: A Study, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Evolutionary Computation Algorithms for Cryptanalysis: A Study will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-153365