Black Hole Attack Detection in Vehicular Ad Hoc Networks Using Statistical Process Control
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A vehicular ad-hoc network (VANET) is a communication network designed to make vehicles communicate with each other in order to exchange useful information that makes driving easier. This communication is exposed to several vulnerabilities such as Denial of Service attacks (DOS). Among the most known attacks are the Black Hole attacks. A malicious user who performs the attack can intercept the data and destroys it without forwarding it to their destination. This can cause a serious damage when the information concerns a serious incident. In this paper, we propose a new method to detect the black hole attack during communication in a VANET environment using a statistical process control (SPC). The proposed method operates in real time by monitoring network activity with graphical representations to detect abnormal deviations.
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