A Method of Detecting Camouflage Data with Mutual Vehicle Position Monitoring

Shuntaro Azuma (1) , Manabu Tsukada (2) , Teruaki Nomura (1) , Kenya Sato (1)

1 Doshisha University [Kyoto]
2 UTokyo - The University of Tokyo

Due to the development of V2V communication, such safe driving support as collision prevention and adaptive cruise control has been achieved. Furthermore, in recent years, in addition to infrastructure-to-vehicle communication (V2I communication) and communication with a cloud server using mobile lines is also possible (V2C communication), and such communication is generally called V2X communication. Through V2X communication, vehicle's peripheral information can be shared with other vehicles on a cloud server. However, the influence of inappropriate information on the cloud must be addressed. By faking vehicle information, a system using a cloud server, perhaps deliberately causing congestion and/or accidents. In this research, we propose a method that detects camouflage data from all of that aggregated data on a cloud server using V2X communication and utilizing the surrounding vehicle information. We also analyze possible threats and the requirements for the data that are sent to a cloud, clarify security, and evaluate the proposed method's implementation. We detected 93% of the camouflage data, and improved the detection rate 100% by increasing the threshold value of the proposed method and, enhancing the effect of guaranteeing the data's reliability. Furthermore, we showed the false positives of the proposed method and its execution processing time and examined feasibility.

Mots clés: vehicle security; V2X communication; detecting camouflage data

Domaines: Robotique [cs.RO]; Réseaux et télécommunications [cs.NI]; Informatique mobile

Shuntaro Azuma, Manabu Tsukada, Teruaki Nomura, Kenya Sato. A Method of Detecting Camouflage Data with Mutual Vehicle Position Monitoring. The Sixth International Conference on Advances in Vehicular Systems, Technologies and Applications (VEHICULAR 2017), Jun 2017, Nice, France. pp.48-53. ⟨hal-01879103⟩