12th EAI International Conference on Mobile Multimedia Communications, Mobimedia 2019, 29th - 30th Jun 2019, Weihai, China

Research Article

Trust prediction based on grey exponential smoothing method in VANETs

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  • @INPROCEEDINGS{10.4108/eai.29-6-2019.2282065,
        author={Sanshun  Zhang and Li  Li and Hui  Xia and Rui  Zhang and Ye  Li},
        title={Trust prediction based on grey exponential smoothing method in VANETs},
        proceedings={12th EAI International Conference on Mobile Multimedia Communications, Mobimedia 2019, 29th - 30th Jun 2019, Weihai, China},
        publisher={EAI},
        proceedings_a={MOBIMEDIA},
        year={2019},
        month={6},
        keywords={vehicular ad hoc network; trust prediction; grey model; routing protocol},
        doi={10.4108/eai.29-6-2019.2282065}
    }
    
  • Sanshun Zhang
    Li Li
    Hui Xia
    Rui Zhang
    Ye Li
    Year: 2019
    Trust prediction based on grey exponential smoothing method in VANETs
    MOBIMEDIA
    EAI
    DOI: 10.4108/eai.29-6-2019.2282065
Sanshun Zhang1, Li Li1, Hui Xia1,*, Rui Zhang1, Ye Li1
  • 1: Shandong Provincial Key Laboratory of Computer Networks, Shandong Computer Science Center (National Supercomputer Center in Jinan), Qilu University of Technology (Shandong Academy of Sciences)
*Contact email: xiahui@qdu.edu.cn

Abstract

In vehicular ad hoc networks (i.e., VANETs), normal communications between vehicles are vulnerable to attacks from malicious vehicles. Trust-based solution is a feasible method to solve the routing security problem. In this paper, a trust prediction model based on grey exponential smoothing method is proposed by combining the grey model, the exponential smoothing prediction method and the golden section search method. A multicast routing protocol based on the grey exponential smoothing trust prediction model, named ESGM-ODMRP, is presented to verify the validity of this new method. In the experiments, the evaluation of four routing metrics (i.e., packet delivery ratio, overhead, average latency and byte sent per byte delievered) prove that our protocol performs better in identifying malicious vehicles and establishing secure routes.