###### Abstract
The purpose of this attack could be to cause detriment of the performance of the network or to harm the legitimate vehicles themselves. Another form of attack that proves dangerous in the network is that of a wormhole attack [7]. This is somewhat similar to the black hole attack, in which at least two malicious attacker nodes place themselves in an optimum position to enhance the damage of their attack and form a tunnel with the lowest number of hop counts to entrap other legitimate vehicles for opting for the attacker's tunnel route. Once the legitimate vehicles start sending messages through the attacker's route, the malicious nodes can do anything with the received information; they can either drop the message, modify it, redirect it, or eavesdrop on it. Position falsification attack [8] is another critical attack that can be deployed in connected vehicles. In this attack, the malicious attacker broadcasts false information regarding the position of the vehicles through safety messages that are generated on a periodic basis. This attack can create confusion among the connected vehicles and can cause severe repercussions. Safety applications are being deployed in the vehicular network to achieve the required safety and convenience for individuals. For these applications to work optimally and stay up to date, connected vehicles need to be made aware of their surrounding environment through BSMs. Through these messages, the connected vehicles are updated about their surroundings and make appropriate decisions regarding any event. The BSMs need to be generated and transmitted in real time because they become irrelevant after a certain period of time, e.g., the information about a vehicle's speed and location may be useless after an hour or two later unless it is used by law enforcement authorities. Due to the time-criticality, these messages are often not encrypted. Some mechanisms may encrypt BSM as well, but at the cost of the network performance [9]. These BSMs are exposed to various attacks that can be initiated in the network which can cause severe harm to the victims. Figure 1 shows a scenario in which the RSU detects an attacker vehicle and relays information to other RSUs and vehicles. Our proposed scheme uses the multi-BSM approach for anomaly detection; more specifically, position falsification attacks. The proposed scheme compares multiple consecutive BSMs from the same vehicles based on multiple parameters, i.e., location, speed, and direction. It is assumed that all RSUs are linked with each other and are connected with a central database. It is also assumed that Global Positioning System (GPS) systems of genuine vehicles are working correctly. Only malicious vehicles tamper with the GPS data. Our work targets the detection and prevention of position falsification attacks in a connected vehicular environment. The salient features of the papers are following:  
* The detection of position falsification attacks using multiple consecutive BSMs utilizing parameters such as position, speed, and direction is proposed. * The RSUs are used for the detection of position falsification attacks, as onboard units (OBUs) of the vehicles have limited resources and may not be connected to the central database in real time. * Preventing vehicles from falling victims to the attacks of a malicious node even before entering the transmission range of the attacker with the help of RSUs. Section 2 reviews the work that has been accomplished in the connected vehicles regarding anomaly detection and security attacks. The preliminaries and the system model are discussed in Section 3. The proposed scheme is elaborated in Section 4. After that, performance evaluation is discussed in Section 5, followed by conclusion and future work in Sections 6 and 7. Lastly, acknowledgments are addressed.