Just-in-Time Memoryless Trust for Crowdsourced IoT Services
This addresses trust management for IoT service users, but it appears incremental as it builds on existing trust assessment concepts with a memoryless and session-specific approach.
The paper tackles the problem of evaluating trustworthiness in crowdsourced IoT services by proposing a just-in-time memoryless trust framework that assesses trust without prior knowledge, using service-session data for current session validity, and reports efficiency gains from experiments.
We propose just-in-time memoryless trust for crowdsourced IoT services. We leverage the characteristics of the IoT service environment to evaluate their trustworthiness. A novel framework is devised to assess a service's trust without relying on previous knowledge, i.e., memoryless trust. The framework exploits service-session-related data to offer a trust value valid only during the current session, i.e., just-in-time trust. Several experiments are conducted to assess the efficiency of the proposed framework.