Just-in-Time Memoryless Trust for Crowdsourced IoT Services

TL;DR

This paper introduces a novel just-in-time memoryless trust framework for crowdsourced IoT services, enabling real-time trust evaluation without prior knowledge, tailored to session-specific service conditions.

Contribution

It presents a new trust assessment method that operates without historical data, specifically designed for dynamic IoT environments, enhancing real-time decision-making.

Findings

Framework effectively evaluates trust during current sessions

Experimental results demonstrate high accuracy and efficiency

Trust values are reliable for immediate service assessment

Abstract

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.