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Fox-Hole Model for Data-centric Misbehaviour Detection in VANETs

Broadcasting false traffic information in VANETs is one of the major security concerns. Detecting false data sent by misbehaving nodes has been a major challenge in recent times. In this paper, we are going to present a simple scheme for detection of correctness of information regarding happening of an event like a road crash. It uses the data collected from the movement of other vehicles on the road who can observe the event and measuring their response towards it. Our misbehaviour detection scheme (MDS) is data-centric meaning it figures out whether the information received is true. Vehicles may send false information just to gain access to a whole lane in a congested area. For fast moving traffic, it thus becomes more important to find the truth-value of a broadcasted alert rather than exactly finding the misbehaving node. Our scheme is not based upon voting but observing the actual movement of nodes in response to the detected event. After describing the model in detail and the mathematical equation behind the MDS, we will present certain scenarios as a justification of our scheme. At the end, we will highlight the advantages and certain limitations of our MDS as a comparative study.