LAUSR

Using vehicular ad-hoc network, smart vehicles can detect dangerous events on the road and announce warnings to other vehicles to ensure road safety. The other vehicles nearby may receive the warning messages and accordingly choose a different route. But, because of the presence of malicious users on the road and errors in the detection system, some warning messages may prove dubious. Therefore, to distinguish between genuine and dubious messages, an element of trust has to be infused into the warning system. One common approach for this is to enable the receivers count the popularity of the reports of a warning event, i.e., the trust level. Once the trust level meets a predefined threshold, the vehicle's on-board unit will trust the warning event and warn the driver. Yet, owing to security and privacy concerns, anonymous counting problem does exist, because it is hard to fulfill both anonymity and counting requirements. In this paper, the authors define the anonymous counting problem and then propose a conditional distinguishable pseudo identities scheme that achieves conditional anonymity to overcome the counting problem. To achieve this feature of pseudo identities, time slot was added to minimize the influence of the adversary. Randomized batch verification was applied to enhance efficiency. Furthermore, it is shown how to achieve those features and provide proof on pairing equations. Finally, the time complexity of the proposed scheme was analyzed and its performance evaluated by Simulation of Urban Mobility.