Applicable Image Security Based on Computational Genetic Approach and Self-Adaptive Substitution

Abstract

With the emergence of new information technology fields and various usages of internet applications, securing massive amounts and multiple varieties of multimedia data has become a significant challenge. Hence, it is essential to investigate and develop new cryptographic algorithms to ensure the protection and privacy of multimedia data at rest and during transmission through the communication channel while attempting to overcome the limitations of traditional cryptographic methods. This paper suggests a novel image encryption and decryption technique based on a computational genetic approach and selfadaptive chaotic substitution. The proposed encryption method depends mainly on four steps: sequence generation, diffusion, confusion, and optimization. The USC-SIPI image dataset is being utilized to prove the correctness and effectiveness of our approach in defending against different attack types. Furthermore, the proposed technique could be capable of withstanding attacks while achieving an information entropy of 7.999, Number of Pixel Change Rate of 99.62%, and a Unified Average Change in Intensity of 33.54%, respectively. The results of security testing and analysis revealed that our image security method is strongly recommended for modern communications security applications.INDEX TERMS Image security, chaotic systems, computational methods, genetic algorithm. I. INTRODUCTIONWith the development of the Internet and computer technology, people are using applications and systems in many aspects of their daily life. These applications and systems depend entirely on multimedia data (e.g., texts, images, videos, and audio). Multimedia data carries all kinds of information. This critical information may be private, medical, civil, military, industrial records, or secret messages and is primarily a target of many attacks. Illegal use of data can lead to major problems for users and organizations. Thus, multimedia data must be protected before transmission or distribution over networks.Various digital images and information formats, like color, gray, binary, and medical images, have been used and The associate editor coordinating the review of this manuscript and approving it for publication was Shuangqing Wei .

Multi‐chaotic maps and blockchain based image encryption

“…The random behavior of the chaotic maps (logistic map and tent map) used in the proposed system has been validated by the National Institute of Standards and Technology (NIST) test. The NIST randomness test has 15 statistical tests with every test having a p‐ value (randomness probability) 31 . Therefore, NIST analysis has been considered for testing the randomness of the chaotic sequences generated by the logistic map and tent map shown in Tables 2 and 3.…”

“…The NIST randomness test has 15 statistical tests with every test having a p-value (randomness probability). 31 Therefore, NIST analysis has been considered for testing the randomness of the chaotic sequences generated by the logistic map and tent map shown in Tables 2 and 3.…”

Exploiting Dynamic Vector-Level Operations and a 2D-Enhanced Logistic Modular Map for Efficient Chaotic Image Encryption

“…Consequently, image encryption research utilizing new technologies and methods has been increasingly attracting attention from researchers due to various reasons, such as privacy protection, commercial security, and military security [ 4 ]. In the past few years, to offer more efficient and secure protection for image data, lots of new image encryption algorithms or schemes have been continuously suggested [ 5 , 6 , 7 , 8 , 9 , 10 ]. For these newly proposed image encryption algorithms or schemes, this paper will collectively refer to them as encryption schemes hereafter.…”

Autonomous Self-Adaptive and Self-Aware Optical Wireless Communication Systems

“…Understanding self-awareness and self-adaptive functions is the cornerstone of modeling, designing, and engineering future systems. The self-awareness concept has been applied in many disciplines, such as computing systems [6], artificial neural networks [5], Internet of Things networks [7], and image security [8].…”