Description

Rapid digital advances have made image security crucial, especially in fields like banking, biometrics, and social media. This study proposes a novel image cryptosystem combining DNA and chaos-based cryptography to ensure secure image transmission. A Cross Cosine Map (CCM) generates chaotic keys for grayscale image encryption, while a hyper-chaos-based system secures color images. A lightweight architecture offers dual-layered protection for biometric data. The system’s performance is validated using statistical, differential, and robustness analyses, along with standard image quality metrics.

About Author

Sujarani Rajendran obtained her M.Tech and Ph.D. degrees in Computer Science from SASTRA Deemed University, Thanjavur, Tamil Nadu, India, in 2010 and 2021, respectively. She obtained her M.C.A. degree from Annamalai University in 2008. She is currently working as an Assistant Professor in the Department of Computer Science at SASTRA Deemed University, Kumbakonam. Her research interests include Chaotic Cryptography, Steganography, Wireless Sensor Networks, Machine Learning, and Deep Learning. She has published many articles in SCIE- and SCOPUS-indexed journals and has also presented articles at various international conferences.

Manivannan Doraipandian received his B.E. in Electrical and Electronics Engineering from Bharathidasan University, Trichy, Tamil Nadu, India (1996), and his M.Tech in Computer Science and Engineering (2002) from SASTRA University, Tamil Nadu, India. He is currently working as Associate Dean of the Computer Science Department, School of Computing, at SASTRA University, Tamil Nadu, India. His academic research interests include cryptography, security in embedded systems, and Wireless Sensor Networks using ARM processors and embedded communication systems. In recent years, his research has focused on platforms capable of handling low-power processors for Wireless Sensor Nodes and applications in distributed embedded platforms, as well as information security topics in the embedded systems domain.