Chaos-Based Image Encryption Using Refined Hash Function

Source abstract

This study presents an enhanced chaos-based image encryption framework that integrates refined hash functions to address modern challenges in secure image transmission and cryptographic robustness. Conventional encryption techniques often struggle to defend against sophisticated cyberattacks and ensure data integrity, especially in critical applications such as medical imaging and IoT security. The proposed encryption system combines the inherent unpredictability of chaotic systems with advanced hashing mechanisms to develop a robust security framework. A chaos generator and mapping function produce high-quality chaotic signals, which are transformed into the cryptographic domain to enhance encryption strength. The refined hash function incorporates image-specific attributes, generating unique and highly sensitive hash values capable of detecting even the slightest data alterations. The encryption system is implemented in Python, leveraging its extensive cryptographic libraries for precision and efficiency. Performance evaluation is conducted using statistical metrics such as histogram analysis, adjacent pixel autocorrelation, and key sensitivity tests, which reveal significant improvements in randomness and robustness against differential attacks. Experimental results indicate an NPCR of 99.81%, UACI of 33.69%, and Shannon entropy of 7.998, demonstrating superior encryption quality compared to traditional methods. Additionally, the proposed system achieves faster execution times, making it suitable for real-time applications requiring high security and computational efficiency. This research contributes to cryptography by proposing a scalable and efficient encryption model that mitigates existing vulnerabilities while ensuring robust protection of sensitive data. The practical applications of this system extend to secure communications, healthcare data protection, and IoT security, where confidentiality and integrity are paramount. By addressing critical gaps in traditional encryption techniques, this study provides a foundation for develo