Vehicular Ad Hoc Networks are self-organizing Peer-to-Peer networks that typically have highly mobile vehicle nodes, moving at high speeds, very short-lasting and unstable communication links. VANETs are formed without fixed infrastructure, central administration, and dedicated routing equipment, and network nodes are mobile, joining and leaving the network over time. So, VANET-security is very vulnerable for the intrusion of malicious and misbehaving nodes in the network, since VANETs are mostly open networks, allowing everyone connect, without centralized control. In this paper, we propose a rough set based anomaly detection method that efficiently identify malicious behavior of vehicle node activities in these VANETs, and the performance of a proposed scheme is evaluated by a simulation in terms of anomaly detection rate and false alarm rate for the threshold ${epsilon}$.