Abstract

In this paper, a novel image encryption scheme is proposed based on combination of pixel shuffling and new modified version of simplified AES. Chaotic baker’s map is used for shuffling and improving S-AES efficiency through S-box design. Chaos is used to expand diffusion and confusion in the image. Due to sensitivity to initial conditions, chaotic baker’s map has a good potential for designing dynamic permutation map and S-box. In order to evaluate performance, the proposed algorithm was measured through a series of tests. These tests included visual test and histogram analysis, randomness test, information entropy, encryption quality, correlation analysis, differential analysis and sensitivity analysis. Experimental results show that the new cipher has satisfactory security and is more efficient than AES which makes it a potential candidate for encryption of multimedia data.

Highlights

  • Visual information and imagery play an important role in almost all areas of our lives

  • Baker’s map is used to generate a permutation matrix, which is in turn used to generate S-box in the S-AES algorithm

  • The number of occurrence for each grey level in the image is not changed after pixel shuffling

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Summary

Introduction

Visual information and imagery play an important role in almost all areas of our lives. In this research we have tried to find a simple, fast and secure algorithm for image encryption using the characteristics of chaotic functions and the possibility of creating very long length keys. According to key’s large space in the chaotic functions, this method is very robust. This algorithm is very sensitive to small changes in key so even with the knowledge of the key approximate values; there is no possibility for the attacker to break the cipher.

Chaos and cryptography
Methods
Simplified AES
The proposed algorithm
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Security analysis
Visual test and histogram analysis
Randomness test
Information entropy
Measurement of encryption quality
Correlation coefficients analysis
Difference between cipher and plain-images
Key sensitivity analysis
Findings
Conclusion
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