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Breaking Knapsack Cipher Using Population Based Incremental Learning | ||
| Journal of Al-Nahrain University - Science | ||
| Article 1, Volume 14, Issue 2, 2011, Pages 199-209 | ||
| Author | ||
| Nasreen J. Kadhim | ||
| Abstract | ||
| The demand for effective internet security is increasing exponentially day by day. Businesseshave an obligation to protect sensitive data from loss or theft. Such sensitive data can be potentiallydamaging if it is altered, destroyed or if it falls into the wrong hands. So they need to develop ascheme that guarantees to protect the information from attacker. Cryptology which is the scienceand study of systems for secret communication is at the heart of providing such guarantee. Breakingknapsack cipher using Population Based Incremental Learning (PBIL) is suggested in this paper.Results of this implementation are compared with results of Poonam Grag, Aditya Shastri, and D.C.Agarwal (2006) which had made an enhancement on the efficiency of genetic algorithm attack onknapsack cipher suggested by Spillman in 1993. The result of comparison shows that PopulationBased Incremental Learning has less complexity and enjoys high speed (i.e. correct results will begenerated with less number of generation compared to that generated using genetic algorithm) alsothe overhead for genetic algorithm operations is significantly higher than for Population BasedIncremental Learning. | ||
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