Soft Computing-Driven Framework for Enhanced Security in Medical Image Transmission

Abstract

Ensuring the security of medical image transmission (SoMIT) is vital in healthcare settings, as it protects sensitive patient and healthcare data, enabling doctors to provide accurate and efficient treatment and optimal care. This research focuses on enhancing SoMIT over hospital communication networks using a soft computing-driven framework (Hybrid Fuzzy-AHP) method within the Multiple-Criteria Group Decision Making (MCGDM) technique. The Hybrid Fuzzy-AHP method considers five critical medical image security (MIS) parameters: integrity [MS1], authentication [MS2], confidentiality [MS3], access control [MS4], and availability [MS5]. Furthermore, this soft computing technique assigns weighted prioritization to each MIS parameter, indicating that integrity holds the highest impact, followed by authentication, confidentiality, access control, and availability. The MIS optimization outcome of 0.8075 signifies robust security according to the triangular fuzzy number (TFN) scale. These MIS security outcomes were validated using GNU Octave and MATLAB tools. Additionally, a comparison between the proposed Hybrid Fuzzy-AHP method and various MCGDM techniques shows that the proposed method outperforms other MCGDM techniques. This research significantly contributes to the development of secure and efficient medical image transmission (MIT) systems. The findings of this research have important implications for healthcare providers, enhancing the security and efficiency of MIT while improving the accuracy of patient treatments.