###### Abstract  
With the dawn of the emerging technologies in the field of vehicular environment, connected vehicles are advancing at a rapid speed. The advancement of such technologies helps people daily, whether it is to reach from one place to another, avoid traffic, or prevent any hazardous incident from occurring. Safety is one of the main concerns regarding the vehicular environment when it comes to developing applications for connected vehicles. Connected vehicles depend on messages known as basic safety messages (BSMs) that are repeatedly broadcast in their communication range in order to obtain information regarding their surroundings. Different kinds of attacks can be initiated by a vehicle in the network with malicious intent by inserting false information in these messages, e.g., speed, direction, and position. This paper focuses on the position falsification attacks that can be carried out in the vehicular environment and be avoided using the multi-BSM approach. Multi-BSM uses consecutive multiple BSMs with different parameters to detect and warn other vehicles about position falsification attacks. Multi-BSM is compared to other anomaly detection algorithms and evaluated with rigorous simulations. Multi-BSM shows a high level of anomaly detection, even in high vehicle density, with up to 97% accuracy rate compared to the respective algorithms. s 2022  
disseminated flawlessly in connected vehicles, but in actuality, this information is vulnerable to attacks initiated by malicious attacker vehicles present in the network. Schemes need to be adopted to counter and detect attacks that are currently exploiting the network. In [2], the authors surveyed identity-based cryptographic schemes used for the security and privacy concerns in VANETs. The protection and safeguarding of the regular updates are as vital as the important messages that are disseminated in a timely manner, as any potential attacker could be listening in on the regular updates of the connected vehicles and could launch different types of attacks depending on the attacker's intention. In [3], the authors proposed a secure data-sharing scheme for 5G-enabled vehicular networks without using the RSUs. Preventive measures need to be implemented to avoid any misfortunes. These attacks could harm individuals either directly or indirectly. The attacks could be active in nature, in which the attacker modifies the contents of the messages being disseminated, or the attack could be passive, in which the attacker just listens to the information being conveyed from one end to the other and uses it for its personal gains. Mechanisms are needed to check for anomalies in the behavior of the connected vehicles present in the network to detect whether they are legitimate vehicles or malicious attackers with ill intent. Such disturbances cause harm to the commuters and degrade the performance of the network, and they need to be dealt with swiftly. In [4], the authors proposed a privacy-preserving authentication scheme known as CM-CPPA in 5G-enabled vehicular networks while decreasing the overhead of communication. The vehicular network is exposed to different kinds of attacks, and if preventive measures are not taken then they could harm the individuals directly or indirectly. One such attack is a black hole attack [5], in which the malicious nodes place themselves in a suitable position in the network where the effects of the attacks can be maximized. The malicious nodes pretend to have an optimal route for the dissemination of messages in order to lure more vehicles. When the messages are sent to these malicious nodes, they either drop the messages, redirect them, or use them for their own nefarious purposes. Another attack that is orchestrated by the malicious nodes in the vehicular network is that of a Sybil attack [6]. In this attack, the malicious node initiates the illusion of the existence of multiple vehicles in the network and generates false information in order to take control of the available network.