A Review on Detecting Malacious Node in Urban Vehicular Network

In vehicular Area, where privacy of vehicle, mainly the location of vehicle i.e. privacy of anonymous vehicles, is highly not tracking, nameless verification of vehicles is impossible to discuss or distinction. A malicious node (attacker in network) who tries to forging multiple same false identities of the node available in the network can easily launch an attack called Sybil attack, gaining a suspiciously large influence. In this project , we mentioned a simple Sybil attack occur in the network using the trajectories of vehicles for identification of the node while at rest maintaining the node location privacy in the network. When a node in the vehicular network associates a Road-Side Unit (RSU), it dynamically demands an authorization identity message from the RSU as the proof identity of the vehicle in the Current RSU region. More predominantly, we construct a location-hidden identity authorized message generation scheme for two objectives: first, two authorized identity messages signed by the equivalent RSU within the same given period of time that concerning with each other for provisional purpose are familiar so that they can be used for identification; Second ,Road-Side Unit signatures on messages are signer are different so that the RSU location identity information is hidden from the resulted official message. With the some restriction, official messages from the node used for long-term identification are declined so that at the exacting road side unit its authorization is used as proof of vehicle. With this order on the identity scheme, vehicles keep its location privacy as the identification by taking all the series of Sequence of authorized message. Also vehicle i.e. nodes in the vehicular network generate a location-hidden trajectory for preserving location-privacy identification. Utilizing social relationship among trajectories according to the resemblance definition of two trajectories, detecting attacker node can recognize and therefore discharge “communities” of Sybil trajectories. Rigorous security analysis and widespread tracedriven simulations exhibit the worth of detection attacker.