We propose an integrity-preserving framework for managing trust information in crowdsourced IoT environments. The integrity of trust information is paramount for ensuring accurate trust assessment. Traditional trust frameworks assume that distributed storing entities of trust information are trustworthy, making them vulnerable to internal attacks. In this respect, entities responsible for storing trust data could tamper with information for personal gain and competitive advantage. Trust assessment using such tampered data could lead to inaccurate evaluations and may mislead IoT users within the environment. We propose a novel Tampering Detection Approach (TDA) to identify the tampering in trust information. Furthermore, we propose a technique to discover the tampering sophistication level. A set of experiments is conducted to evaluate the effectiveness and efficiency of the proposed approaches. Results demonstrate that our TDA achieves a 40% accuracy improvement in detecting tampered data compared to state-of-the-art methods.
Lokuruge et al. (Thu,) studied this question.