Please use this identifier to cite or link to this item: https://dspace.iiti.ac.in/handle/123456789/4994
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dc.contributor.authorChaudhari, Narendra S.en_US
dc.date.accessioned2022-03-17T01:00:00Z-
dc.date.accessioned2022-03-17T15:36:23Z-
dc.date.available2022-03-17T01:00:00Z-
dc.date.available2022-03-17T15:36:23Z-
dc.date.issued2017-
dc.identifier.citationJain, A., & Chaudhari, N. S. (2017). An improved genetic algorithm for developing deterministic OTP key generator. Complexity, 2017 doi:10.1155/2017/7436709en_US
dc.identifier.issn1076-2787-
dc.identifier.otherEID(2-s2.0-85042203153)-
dc.identifier.urihttps://doi.org/10.1155/2017/7436709-
dc.identifier.urihttps://dspace.iiti.ac.in/handle/123456789/4994-
dc.description.abstractRecently, a genetic-based random key generator (GRKG) for the one-time pad (OTP) cryptosystem has been proposed in the literature which has certain limitations. In this paper, two main characteristics (speed and randomness) of the GRKG method are significantly improved by presenting the IGRKG method (improved genetic-based random key generator method). The proposed IGRKG method generates an initial pad by using linear congruential generator (LCG) and improves the randomness of the initial pad using genetic algorithm. There are three reasons behind the use of LCG: it is easy to implement, it can run efficiently on computer hardware, and it has good statistical properties. The experimental results show the superiority of the IGRKG over GRKG in terms of speed and randomness. Hereby we would like to mention that no prior experimental work has been presented in the literature which is directly related to the OTP key generation using evolutionary algorithms. Therefore, this work can be considered as a guideline for future research. © 2017 Ashish Jain and Narendra S. Chaudhari.en_US
dc.language.isoenen_US
dc.publisherHindawi Limiteden_US
dc.sourceComplexityen_US
dc.titleAn Improved Genetic Algorithm for Developing Deterministic OTP Key Generatoren_US
dc.typeJournal Articleen_US
dc.rights.licenseAll Open Access, Gold, Green-
Appears in Collections:Department of Computer Science and Engineering

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