iDetectLoaD: A Signaling Game-based Security Load Distribution for IoV

With the rapid growth of intelligent networked vehicles, vehicle network security threats are constantly emerging, which makes the demand for VSOC (Vehicle Security Operations Center) increasingly urgent. By analyzing the real-time data sent back by RSU (Roadside Unit) and vehicles, VSOC can realize the data analysis and security protection of automobile privacy data. However, these highly interconnected devices greatly expand the attacked space, making the Internet of Vehicles (IoV) an essential target of cyber attacks. To reduce this threat, many intrusion detection systems have been proposed. However, a specific budget limits the number of VSOC resources dedicated to intrusion detection, and the limited security resources cannot provide comprehensive detection for all devices. In addition, the existing defense mechanism ignores the fact that the defender has the ability to mislead the attacker by sending some signals during the interaction, thus delaying or preventing the attack. This paper proposes a two-stage game model to solve these challenges and introduces two parameters into the utility function to describe complex and realistic scenarios. Specifically, in the first stage, we determine how to allocate the limited detection load, and in the second stage, we design the optimal signaling scheme to manipulate the attacker to take actions beneficial to the defender. The experimental results show that our solution effectively reduces the number of attacks and resource loss compared with the other two classical detection load allocation strategies (namely fair allocation and one-stage Stackelberg).