Medical Image Encryption Through Chaotic Asymmetric Cryptosystem

Abstract

In the era of digital advancements, safeguarding medical data holds significant importance. This article introduces a novel approach to encrypting images through public-key encryption, incorporating the properties of Elliptic Curve Cryptography (ECC) and the Blum-Goldwasser Cryptosystem (BGC). The proposed method capitalizes on the chaotic properties of a sequence generator to augment the randomness in the encrypted image. The encryption process initiates with a secure key exchange mechanism using elliptic curves and the Blum-Goldwasser Cryptosystem. Pixel randomization is achieved through a chaotic map, followed by encryption using ECC and BGC, which integrates the discrete logarithmic problem, probabilistic encryption, and the quadratic residuosity problem. Both ECC and BGC components contribute to unpredictability and complexity, fortifying the security measures. The amalgamation of these cryptographic techniques provides resilience against cyber threats such as brute-force attacks and differential cryptanalysis. Thorough simulations and performance assessments affirm the effectiveness and computational efficiency of this hybrid approach when compared to existing methods. The experimental values of information entropy, average correlation, NPCR and UACI are 7.9998, 0.0010, 99.6901% and 33.5260% respectively. The total time taken for the proposed methodology is 0.142 seconds. These values indicates that the proposed hybrid chaotic image encryption method displays promise for diverse applications.

Keywords

• Blum-Goldwasser cryptosystem
• chaotic encryption
• cryptanalysis
• elliptic curve cryptography
• image encryption
• public key encryption