An intelligent system with fuzzy-based inference engine for secured tele-robotic surgery

Abstract

A new era of technological developments has been ushered in by the growth of the Internet of Things (IoT), with telerobotic systems significantly contributing to the automation of crucial medical, diagnostic, and pharmaceutical processes. This study presents a thorough analysis of access control mechanisms in the context of the IoT to improve the security and usability of these cutting-edge technologies. The Fuzzy Logic Trust-Based Access Control Algorithm (FL-TACA) offers a novel strategy that optimizes energy efficiency and allocates access rights. It offers low-latency operations and data security as a secure communication solution for the telerobotics community. The technique decreases vulnerabilities to denial of service, eavesdropping, and replay attacks by allocating access permissions based on the least privileges. Finally, integrating FL-TACA promises to improve the caliber and effectiveness of patient care by enabling intelligent and independent activities that lessen the workload on medical staff.

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