  Effective applications of vehicular ad hoc networks in traffic signal control
require new methods for detection of malicious data. Injection of malicious
data can result in significantly decreased performance of such applications,
increased vehicle delays, fuel consumption, congestion, or even safety threats.
This paper introduces a method, which combines a model of expected driver
behaviour with position verification in order to detect the malicious data
injected by vehicle nodes that perform Sybil attacks. Effectiveness of this
approach was demonstrated in simulation experiments for a decentralized
self-organizing system that controls the traffic signals at multiple
intersections in an urban road network. Experimental results show that the
proposed method is useful for mitigating the negative impact of malicious data
on the performance of traffic signal control.
