\documentclass[thesis]{thesis-gwu}[2020/02/03]
Open Access DepositedIntelligent Transportation Systems (ITS) play a crucial role in realizing sustainable transportation by addressing traffic congestion and ensuring safe travel experiences. Among the key components of ITS, V2X communication facilitates the exchange of information between vehicles and ITS entities. However, despite its potential benefits, the open wireless nature of V2X communication renders it vulnerable to attacks. In response, many researchers has provided different defense schemes. These schemes often rely on direct interactions to identify malicious vehicles. However, direct experiences of target vehicles are often unavailable due to network disrup- tions or encounters with new users makes these defense out of work. In response, I introduce the Trustcito framework, a recommendation-based trust management system that can be used in every vehicle. This framework continuously monitors potential malicious vehicles by requesting recommendations from other entities and then evaluates them against a predefined threshold. my analysis demonstrates that indirect trust can serve as a valuable complement to direct trust within the proposed model. The performance of proposed model is evaluated by Query-Hit Rate and precision recall metrics. For accuracy, I achieve a high precision of above 70% in every map. Regarding the query-hit rate, if there are many nodes and edges, I can achieve a query-hit rate of over 70%.
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