<p>The vehicular ad-hoc network (VANET) aims to minimize accidents, manage traffic, and provide necessary services while travelling on the road. Cluster based VANET is proven to be the best network structure for reliable vehicular communication. The unusual behaviour of vehicles, such as sending bogus information, generating multiple identities, or denial of services (DoS) in such a highly dynamic scenario, may have catastrophic results, like casualties, property loss, or traffic-related problems. Such unusual behaviour of the vehicle is called misbehaviour. We have considered the misbehaviour where the attacker’s vehicle shows the traffic jam condition on the road via an alert message, called a false alert generation attack, for their selfish intent. In this misbehaviour, the attacker vehicle modifies its position, speed, and flow value to make the jam condition plausible. We have proposed an efficient misbehaviour detection (EMD) scheme to detect such false alert generation attacks in a multi-hop cluster based VANET. The multi-hop structure provides stability in a network, contributing significantly to detecting misbehaviour with high accuracy. Our EMD scheme contains three designed plausibility check methods to separately identify the falsification in position, flow value and speed_CH ambiguity. The misbehaviour detection analysis is done based on combining the output of these designed methods. Our EMD scheme evaluated misbehaviour in realistic road scenarios with different percentages of the detector and attacker vehicles in the network. The results indicate that our EMD scheme has shown a 2% to 10% improvement in accuracy in comparison to the SMN scheme, and up to 17% and 40% have been recorded in comparison to the DLB and JCM schemes, respectively, in the presence of 10% to 30% attackers and detector vehicles on 100m to 300m transmission ranges.</p>