Research On Sybil Attack Detection Mechanism Using Beacon Information In VFC

Vehicular Fog Computing(VFC)is proposed to overcome the efficient communication and computation challenges posed by the emergence of the latest applications for vehicles.The main communication method in VFC is consistent with traditional vehicular selforganizing networks,where the operational status of the vehicle is coordinated through beacon information.This has led to the ability of some attackers to launch attacks on vehicle wireless communication networks by forging or replaying beacons.One of the most threatening is the Sybil attack.The attacker can obtain the normal beacons in the vehicle wireless communication network through sniffing and forge or replay the normal beacons,thus generating multiple Sybil nodes in the network.The presence of Sybil nodes can affect the normal vehicle’s judgment of the operation status of other vehicles around,which can easily cause traffic accidents.In addition,Sybil attacks also affect routing,voting and reputation systems,data fusion,and distributed storage in vehicle communication networks.Therefore the proposed mechanism for Sybil attack detection becomes crucial.In this paper,a comprehensive comparison and analysis of existing Sybil attack detection mechanisms in VFC is carried out,and a Sybil attack detection mechanism using beacon information in VFC is designed.This detection mechanism includes Sybil node detection mechanism and malicious node location mechanism.The main research contents are as follows.(1)Research on Sybil node detection mechanism.This paper proposes a general Sybil node detection mechanism in vehicle formation based on car-following model and vehicle motion state similarity.In this detection mechanism,the prediction data of the car-following model and the motion state data of the preceding vehicle are combined through a onedimensional Kalman filter fusion model to obtain the final prediction data.And compare the final predicted data with the data content in the received beacon,and judge whether the beacon is a Sybil node through a threshold.The detection mechanism does not require the assistance of roadside infrastructure,and the vehicle is used as a fog node.It can detect Sybil attacks caused by acceleration,velocity and position forgery.Furthermore,the proposed detection mechanism can be adapted to different vehicle operating conditions.(2)Research on malicious node location mechanism.This paper proposes a malicious node location mechanism based on RSSI and improved trilateration method.The mechanism selects distance estimation technology based on Received Signal Strength Indicator(RSSI)and position estimation technology based on improved trilateration as the positioning scheme.And design the reference node position and distance prediction scheme.According to the above scheme,the distance from the known reference node to the malicious node is estimated by RSSI,and then the coordinates and distance of the predicted reference node are obtained by the reference node position and distance prediction scheme.Input the above information into the improved trilateration method to calculate the location coordinates of malicious nodes.This mechanism does not require RSU assistance,reduces the number of reference nodes required for positioning,and solves the problem of inability to locate caused by collinear reference nodes or inaccurate distance measurement.The experimental results show that the Sybil node detection mechanism proposed in this paper has stable and outstanding detection capabilities under different forgery amplitudes and Sybil proportions.The proposed malicious node location mechanism has excellent location capabilities in different attack modes and ranges.