4.8 Article

A chaos-based probabilistic block cipher for image encryption

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ELSEVIER
DOI: 10.1016/j.jksuci.2018.09.015

Keywords

Probabilistic; Symmetric; Image encryption; Block cipher; Customizable block-size; Chaos

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Traditional encryption may generate the same cipher text, making it vulnerable to replay attacks. Probabilistic encryption, especially the chaos-based probabilistic symmetric encryption proposed in this paper, enhances security by generating different cipher texts each time. This scheme is efficient and customizable, suitable for image encryption, offering high strength against statistical and cryptanalytic attacks.
Traditional encryption is based on secrecy provided by secret-key. But this leads to generation of same cipher text when the encryption scheme is applied to same plaintext with same key. Thus, replay of messages can be effortlessly identified by an adversary which can be a weak link in any communication. Probabilistic encryption is an approach to overcome this weakness where different cipher texts are generated each time same plaintext is encrypted using the same key. Extending the probabilistic approach, which is generally employed in asymmetric encryption, this paper proposes a new chaos-based probabilistic symmetric encryption scheme with customizable block-size suitable for image encryption. It employs a Random Bits Insertion phase followed by four rounds of two-staged diffusion involving simple XOR (exclusive-OR) operation making it computationally efficient. Random Bits Insertion makes the scheme probabilistic. This phase also helps in increasing entropy and making intensity distribution more uniform in cipher. The generated cipher text is twice the size of plain text. An increase in cipher text space is inevitable for probabilistic encryption and it provides an advantage as the apparent message space for the attacker is increased. The observations show that the scheme offers high strength to resist statistical and cryptanalytic attacks. (c) 2018 The Authors. Production and hosting by Elsevier B.V. on behalf of King Saud University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

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