Privacy is one of the most important security requirements of VANETs. To avoid being tracked, the idea of pseudonym changes is introduced, which leads to a problem that a malicious vehicle can easily create a new identity without being punished. In this paper, we present a probabilistic method to isolate malicious vehicles with the existence of pseudonym in VANETs. The main idea is to use Bloom filters to record both dishonest and trusted nodes, periodically broadcast these feedbacks and thereby receivers can update their own credits. In our scheme, we assume each car has a tamper-proof device (TPD) carrying out secure operations, such as signing and credit updating. Honest majority is also assumed. A mathematical model is presented to securely evaluate the credit of a node itself with the help of TPD. The credit will then be attached to each important message as a proof of the reliability of the message. We also discuss the potential attacks.
['Bisheng Liu', 'Yiping Zhong', 'Shiyong Zhang']
Probabilistic Isolation of Malicious Vehicles in Pseudonym Changing VANETs