Data Integrity Attacks Against Dynamic Route Guidance in Transportation-Based Cyber-Physical Systems: Modeling, Analysis, and Defense

Real-time route guidance schemes, as one of the critical services in Transportation-based Cyber-Physical Systems, have been introduced to assist travelers in determining optimal routing with low traffic congestion and travel time. To secure the route guidance process, which enables traffic efficiency and safety, in this paper we first investigate security issues of route guidance schemes via modeling and analysis of data integrity attacks on the route guidance process, and then develop corresponding mitigation mechanisms to combat the investigated attack. Via the manipulation of traffic state data measured or generated by compromised vehicles, the data integrity attack can give rise to erroneous predictions of traffic states and induce improper determination of guided routes for vehicles, increasing traffic congestion, and reducing traffic efficiency and safety. We formally model the attack and analyze its impacts on the effectiveness of route guidance schemes. Our results show that the data integrity attack can effectively disrupt route guidance schemes, leading to significant traffic congestion, increased traveling time, and imbalanced use of transportation resources. To mitigate the data integrity attack, we investigate the forged data filtering scheme, in which the forged traffic state data can be filtered out during data delivery in vehicular networks. Extensive performance evaluations are conducted to demonstrate the effectiveness of the proposed forged data filtering scheme in comparing with an exiting scheme.