Adaptive Authentication Factor Selection in the Internet of Things: A Trust-Based Multi-Objective Optimization Approach
Keywords: Multi-Agent Systems, Internet of Things, Authentication, Trust, Multi-Objective Optimization
Abstract: Multi-Agent Systems (MAS) deployed in the Internet of Things (IoT) face significant security challenges due to device heterogeneity and dynamic environments. Traditional authentication mechanisms often fail to address the various trade-offs that arise in resource-constrained environments, which are critical for IoT systems. To address this, we propose a trust-based, multi-objective optimization framework for adaptive authentication factor selection in IoT. Our approach leverages the Non-Dominated Sorting Genetic Algorithm II (NSGA-II) to optimize the security, energy efficiency, and delay of the authentication factors. Trust is integrated into the optimization model as a guiding parameter to enable a more adaptive and context-aware selection process, ensuring that requirements and resource consumption are tailored to the specific context of each authentication instance. Simulation results demonstrate that our framework enhances security while optimizing resource consumption.
Type Of Paper: Full paper (max page 8)
Anonymous Submission: Anonymized submission.
Submission Number: 23
Loading