A Hybrid Connectionist/ Substitution Approach for Data Encryption

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Author(s): Raed Abu Zitar (Ajman University, UAE)and Muhammed Jassem Al-Muhammed (American University of Madaba, Jordan)
Copyright: 2020
Pages: 20
Source title: Implementing Computational Intelligence Techniques for Security Systems Design
Source Author(s)/Editor(s): Yousif Abdullatif Albastaki (Ahlia University, Bahrain)and Wasan Awad (Ahlia University, Bahrain)
DOI: 10.4018/978-1-7998-2418-3.ch002

Keywords: Artificial Intelligence / Computer Science & IT / Information Science Reference / IT Security and Ethics

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Abstract

The authors believe that the hybridization of two different approaches results in more complex encryption outcomes. The proposed method combines a symbolic approach, which is a table substitution method, with another paradigm that models real-life neurons (connectionist approach). This hybrid model is compact, nonlinear, and parallel. The neural network approach focuses on generating keys (weights) based on a feedforward neural network architecture that works as a mirror. The weights are used as an input for the substitution method. The hybrid model is verified and validated as a successful encryption method.

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