Abstract
In vehicular ad hoc networks, opportunistic routing can effectively improve the reliability and throughput. However, opportunistic routing also has security issues. For example, malicious nodes can easily mix into node candidate sets, which can interfere with network performance. In this paper, a trust model based on node behavior is proposed for solving the problem of malicious nodes in the opportunistic routing and forwarding candidate set. The proposed trust model uses pruning and filtering mechanisms to remove malicious suggestions,and uses dynamic weight calculation methods to combine direct trust and indirect trust when calculating the comprehensive trust value, which can screen and filter low-trust nodes in the network. Then, combining the ETX (Expected Transmission Count) value and the node trust value, an opportunity routing algorithm based on trust model (BTOR) is proposed. Extensive simulation results represent that the algorithm can significantly improve the network performance and reduce the interference of malicious nodes to the network system.
Highlights
At present, vehicular ad hoc network is mainly realized by sensor technology, Internet technology and wireless communication technology
For the recommender with high trust, if its recommendation deviates from the direct trust, it is acceptable within a certain deviation range, for the recommender with low trust, the corresponding acceptable deviation range will Smaller. Among these m indirect trust values, there may be false indirect trust values recommended by malicious nodes
The direct trust valueDTVijof the evaluation subject i to the evaluation object j, and the indirect trust value ITVkij1,ITVkij2, . . . ITVkijn obtained from the neighboring nodes k1, k2, . . . km, get the whole assessment process
Summary
Vehicular ad hoc network is mainly realized by sensor technology, Internet technology and wireless communication technology. Salehi et al [7] proposed a novel opportunistic routing protocol, which selects the hop to send node based on the link transfer probability between nodes, and based on the trust level calculated by the node to other nodes when communicating data packets. S. Ahmed et al proposed a logic-based trust calculation for HTM method used to identify nodes injected with false information in the network [23]. Ahmed et al proposed a logic-based trust calculation for HTM method used to identify nodes injected with false information in the network [23] In this trust model, when neighboring vehicles share messages, the model can identify the credibility of the event. A. DIRECT TRUST In the Internet of Vehicles environment, some of the main methods for malicious nodes to interfere with the network include: discarding data, forwarding false data, and intentionally delaying the forwarding time.
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