Enhancing Biotechnological Data Security: A Chaos Algorithm-Based Method for Spatial Information Hiding in Computer Networks

Abstract

This paper explores the application of chaotic systems to enhance data security in biotechnological data management, addressing inherent vulnerabilities found in traditional cryptographic systems with small key spaces and low security. We introduce a novel approach using spatiotemporal chaotic series for the redistribution and encryption of biotechnological images and data. The chaotic systems applied in our method are categorized into two types: low-dimensional and high-dimensional chaotic systems, each contributing differently to the encryption strength and security robustness. Our study presents two main techniques for data concealment within biotechnological contexts: a chaotic algorithm combined with the Least Significant Bit (LSB) technique, tailored specifically for the secure handling of sensitive biotechnological data. The findings demonstrate that the proposed system is not only effective in enhancing data security but also efficient in its implementation, making it particularly suitable for applications where large volumes of sensitive data require robust protection against unauthorized access. This approach ensures that biotechnological data transmitted over computer networks is securely hidden, maintaining integrity and confidentiality essential for research and commercial applications in biotechnology.