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Data is big. Data is diverse. Data comes in zillion formats. It is important to ensure the safety and security of the shared data. With existing systems limited and evolving, the objective of the current research work is to develop a robust image encryption technique that is adept and effective at handling heterogeneous data and can withstand state-of-the-art hacking efforts such as brute force attacks, cropping attacks, mathematical attacks, and differential attacks. The proposed efficient DNA cryptographic system (EDCS) model presents a pseudorandom substitution method using logistic sine cosine chaotic maps, wherein there is very little correlation between adjacent pixels, and it can decode the image with or without noise, thereby making the proposed system noise-agnostic. The proposed EDCS-based image model using chaotic maps showed enhancements in parameters such as unified average changing intensity (UACI), number of pixels change rate (NPCR), histogram, and entropy when compared with existing image security methods.

Efficient DNA Cryptographic Framework for Secured Data Encryption Based on Chaotic Sequences