Articles written in Sadhana
Volume 47 All articles Published: 12 August 2022 Article ID 0161
An efficient dual-stage pixel-diffusion based multimedia-image encryption using one-type 1D chaotic maps
K ABHIMANYU KUMAR PATRO MADDIKUNTLA PRAVEEN KUMAR BIBHUDENDRA ACHARYA
Multimedia is an appealing and interactive information representation using a mixture of images, text, audios, and videos. In many cases, people are using images more often than text to represent the information. This is because people do not like to read large amounts of textual content. Multimedia-images arewidely used in military intelligence, satellite imagery, education, business presentations, secret documentations, etc. Security is therefore a major concern nowadays for storing and transmitting these multimedia-images. Thereare many algorithms that have been proposed in recent times to attain security. This paper presents a dual-stage pixel-diffusion protection image encryption method based on one-type one-dimensional (1D) chaotic maps. Thetwo-stage diffusion process diffuses pixels twice and thus increases the algorithm’s security. The proposed algorithm is stronger than the encryption algorithms based on the one-stage diffusion process. The proposed technique initially performs pixel-permutation operation in the individual components of colour images (red, green, and blue) and then conducts twice-diffusion operations (ADD and Exclusive-OR) in the individual components. The performance of the suggested method is evaluated using key space, histogram variance, adjacent pixel correlation, information entropy, differential attack, and computational complexity analyses. The key space of the proposed approach is 70.62% greater than that of the comparative method, which has the greatest key space. Like key space, the proposed strategy has a 4.91% lower histogram variance and 75% lower adjacent pixel correlations in encrypted images than the comparison methods, which has the lowest histogram variance and adjacent pixel correlations. The proposed scheme’s information entropy is just 0.0013% lower than the comparison technique, which has a greater information entropy. The proposed scheme’s average NPCR (Number of Pixel Changing Rate) and UACI (Unified Average Changing Intensity) are 0.01% and 0.002% higher, respectively, than the comparison technique, which has the highest NPCR and UACI value. The suggested approach has a computational complexity that is three times lower than that of the other colour image encryption schemes. According to computer simulations, security analysis findings, and comparison analysis, the proposed methodology outperforms existing image encryption approaches. In addition to improved security, the usage of one type of 1D chaotic maps increases the system’s hardware and software efficiency.
Volume 47 All articles Published: 26 October 2022 Article ID 0213
Hardware-software co-design framework of lightweight CLEFIA cipher for IoT image encryption
PULKIT `SINGH K ABHIMANYU KUMAR PATRO RAHUL KUMAR CHAURASIYA BIBHUDENDRA ACHARYA
Internet of things (IoT) connects a huge number of small devices across a network. End-to-end security is becoming highly crucial as IoT deploys these devices. In this paper, two hardware architectures for CLEFIA cipher are proposed that are capable of providing robust security to encrypt image input under resource-constrained IoT applications. The proposed round-based and pipelined implementations yield better throughput for high-speed applications. In addition, the proposed round-based and pipelined architectures improve maximum operating frequency by 52.95% and 117.22% for Artix-7 FPGA family. The ASIC implementation results show a 39.22% and 51.92% improvement in hardware efficiency over state-of-the-art design, respectively. Moreover, these proposed architectures have been utilized to encrypt images by selecting variable tile sizes along with the control unit. This paper also explores the security of images encrypted by the proposed hardware architecture of the CLEFIA cipher. The existing solutions were compared to correlation coefficients,NPCR, UACI, MSE, PSNR and entropy values.
Volume 48, 2023
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