BIBRM: A Bayesian Inference Based Road Message Trust Model in Vehicular Ad Hoc Networks
New generation wireless sensor networks are demanding in in-time updating. Traditional trust evaluation is based entities and needs lengthy time to establish. The data security would be neglected in entity-based sensor networks. False data is another problem because it is hard to be filtered in these entity-based trust mechanisms. The propagation of false data and redundant information wastes a lot of system energy. This paper proposes a new notion to address these challenges: data-centric trust evaluation mechanism (DTSN) and a new method: Proof-of-Reputation-Relevance (PoRR) to realize DTSN. This trust evaluation mechanism protects both entities and data via authentic consensus on event reports and aggregate related reports’ trust via DST. Then DTSN decision logic makes a decision according to the output of DST. Performance evaluation and security analysis confirm the efficiency and security of the proposed mechanism.