Chaos based efficient selective image encryption

Khan, Jan Sher; Ahmad, Jawad

Abstract

Due to social networks, demand for sharing multimedia data is significantly increased in last decade. However, lower complexity and frequent security breaches on public network such as Internet make it easy for eavesdroppers to approach the actual contents without any hurdle. Many encryption algorithms has been developed by researchers to increase the security of such traffic and make it difficult for eavesdroppers to access actual data. However, these traditional algorithms increase the communication overhead, computational cost and also do not provide security against new attacks. These issues in recent algorithms motivate the researchers to further explore this area and proposed such algorithms which have lower overhead, more efficiency than the existing techniques and equip with requirements of next generations multimedia networks. To address all these issues and keeping in mind the future of next generation multimedia networks, we proposed a secure and light-weight encryption scheme for digital images. The proposed technique initially divide plaintext image in a number of blocks and correlation coefficients of each block are then calculated. The block with the maximum correlation coefficient values are pixel-wise XORed with the random numbers generated from a skew tent map based on a pre-defined threshold value. At last, the whole image is permuted via two random sequences generated from TD-ERCS chaotic map. Experimental results shows higher security via checking correlation, entropy, histogram, diffusion characteristic and key sensitivity of the proposed scheme.

• Journal Article Type: Article
• Acceptance Date: May 18, 2018
• Online Publication Date: May 24, 2018
• Publication Date: 2019-04
• Deposit Date: Sep 13, 2019
• Journal: Multidimensional Systems and Signal Processing
• Print ISSN: 0923-6082
• Electronic ISSN: 1573-0824
• Publisher: Springer
• Peer Reviewed: Peer Reviewed
• Volume: 30
• Issue: 2
• Pages: 943-961
• DOI: https://doi.org/10.1007/s11045-018-0589-x
• Keywords: Signal Processing; Hardware and Architecture; Software; Applied Mathematics; Artificial Intelligence; Information Systems; Computer Science Applications
• Public URL: http://researchrepository.napier.ac.uk/Output/2133529