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A New Heuristic Based on the Cuckoo Search for Cryptanalysis of Substitution Ciphers

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Neural Information Processing (ICONIP 2015)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9490))

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Abstract

The efficient utilization of one of the latest search heuristic, namely, cuckoo search for automated cryptanalysis (or attack) of substitution ciphers is addressed. A previously proposed genetic algorithm based attack of the simple substitution cipher is enhanced. A comparison is obtained between various attack algorithms that are based on cuckoo search, genetic algorithm, enhanced genetic algorithm, tabu search and scatter search where cuckoo search shows the best performance. It is worth pointing out that the proposed cuckoo search algorithm provides a valid and efficient option for solving similar permutation problems.

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Authors and Affiliations

  1. Discipline of Computer Science and Engineering, Indian Institute of Technology Indore, Indore, India

    Ashish Jain & Narendra S. Chaudhari

  2. Visvesvaraya National Institute of Technology Nagpur, Nagpur, India

    Narendra S. Chaudhari

Authors
  1. Ashish Jain
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  2. Narendra S. Chaudhari
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Corresponding author

Correspondence to Ashish Jain .

Editor information

Editors and Affiliations

  1. University of Istanbul, Istanbul, Turkey

    Sabri Arik

  2. University at Qatar, Doha, Qatar

    Tingwen Huang

  3. Tunku Abdul Rahman University College, Kuala Lumpur, Malaysia

    Weng Kin Lai

  4. University of Science Technology, Wuhan, China

    Qingshan Liu

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© 2015 Springer International Publishing Switzerland

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Jain, A., Chaudhari, N.S. (2015). A New Heuristic Based on the Cuckoo Search for Cryptanalysis of Substitution Ciphers. In: Arik, S., Huang, T., Lai, W., Liu, Q. (eds) Neural Information Processing. ICONIP 2015. Lecture Notes in Computer Science(), vol 9490. Springer, Cham. https://doi.org/10.1007/978-3-319-26535-3_24

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  • DOI: https://doi.org/10.1007/978-3-319-26535-3_24

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-26534-6

  • Online ISBN: 978-3-319-26535-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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