Malicious Data Detection in VANET

Abstract: Vehicular networks are becoming wide technology in traffic system. The entities that are part of a vehicular communication system can be private or public vehicles, road-side infrastructure, and authorities, with the latter considered primarily as network entities. Poorly designed VANETs that permit serious attacks on the network can jeopardize the goal of increased driving safety. The unwanted data can disturb the network communication. The wrong information or inject large volume of data can jam the traffic on roads, this type of data is known as malicious data/unsolicited data. Also, the life safety becomes critical and non trusted behaviour of network. Thus the specific characteristics of VANETs result in hard to address security issues, which make the field of secure inter-vehicular communications. Therefore, we have done work on securing VANET and develop a framework for understanding impact of attack. We tried to detect malicious data under VANET environment. In this thesis work, we will present the techniques that have been proposed so far to ensure accurate data transmission between nodes. VANET have configurable no. of nodes and multiple sensors/actuators. Next, To develop a model of all on board sensors based on their past data set. This may be created by using adapting thresholding, Simulate abnormal behaviour in data arrival rate and volume of data arrival. The Proposed work is related to develop simulator with CAN protocol.

Keywords: Malicious data, VANET attacks, CAN, Intrusion Detection.