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Applications of Intelligent Optimization in Biology and Medicine pp 47–89Cite as

DNA Based Steganography: Survey and Analysis for Parameters Optimization

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Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 96))

Abstract

Nowadays, cryptography and steganography are considered the most famous and secured techniques used in the security field. This chapter introduces a survey on the recent DNA based steganography algorithms that use the DNA as a carrier to enable safe transfer of the critical data over the unsecure network. Some of the recent data hiding techniques based on DNA will be discussed with the main differences between them with respect to some important security parameters such as cracking probability, indicating the algorithm’s strength and weakness. However, some of these techniques do not include the computation of the cracking probability, so each of them will be reviewed and then further analyzed to compute its cracking probability. Then, the issues and the problems in these algorithms are presented and discussed with proposing some solutions and recommendations for achieving optimization in the DNA based steganography field.

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Authors and Affiliations

  1. Faculty of Computer and Information Sciences, Ain Shams University, Cairo, Egypt

    Ghada Hamed, Mohammed Marey, Safaa El-Sayed & Fahmy Tolba

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  1. Ghada Hamed
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  2. Mohammed Marey
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  3. Safaa El-Sayed
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  4. Fahmy Tolba
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Correspondence to Ghada Hamed .

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Editors and Affiliations

  1. Information Technology Department, Cairo University, Giza, Egypt

    Aboul-Ella Hassanien

  2. Department of Information Systems and Computing, Brunel University, London, United Kingdom

    Crina Grosan

  3. Faculty of Computers and information, Ain Shams University, Cairo, Egypt

    Mohamed Fahmy Tolba

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Hamed, G., Marey, M., El-Sayed, S., Tolba, F. (2016). DNA Based Steganography: Survey and Analysis for Parameters Optimization. In: Hassanien, AE., Grosan, C., Fahmy Tolba, M. (eds) Applications of Intelligent Optimization in Biology and Medicine. Intelligent Systems Reference Library, vol 96. Springer, Cham. https://doi.org/10.1007/978-3-319-21212-8_3

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  • DOI: https://doi.org/10.1007/978-3-319-21212-8_3

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  • Online ISBN: 978-3-319-21212-8

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