IEEE Access (Jan 2020)

Context-Aware Quantification for VANET Security: A Markov Chain-Based Scheme

  • Jian Wang,
  • Hongyang Chen,
  • Zemin Sun

DOI
https://doi.org/10.1109/ACCESS.2020.3017557
Journal volume & issue
Vol. 8
pp. 173618 – 173626

Abstract

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Recently, the quantification of VANET security has drawn significant attention due to the lack of standard computational metrics. The salient features of VANET, such as highly dynamic connections, sensitive information sharing, and unreliable fading channels, make the security quantification challenging. Accurate measurement for VANET security depends on the sufficient understanding of “context”, or making sense of the states, environment, or situation. This article proposes a context-aware security quantification scheme for VANET based on the Markov chain. Firstly, a Homogeneous Continuous-Time Markov Chain (HCTMC)-based security state model is designed for VANET. The value of each state of the HCTMC is determined with a value function that incorporates the security strength of transmitted data, dynamic and randomness of the vehicular channel, and transmission delay of the current situated environment of VANETs. Finally, the state transition matrix is derived based on the Homogeneous Discrete-Time Markov Chain (HDTMC) and Homogeneous Poisson Process (HPP). Simulation results show that the security quantification method enables the VANET's system to adopt context-aware defense strategies according to the situated environment.

Keywords