Significant progress in automotive ad hoc networks has been made due to the rapid and considerable advancements in wireless technologies, downsizing, and Internet of Things (IoT) technologies (VANETs). The current intelligent traffic system relies heavily on VANETs and the Internet of Things (ITS). Yet, because of its dynamic nature, decentralised nature, protocol-design-related concerns, and open-access medium, a VANET is extremely susceptible to numerous security assaults. A Black Hole Attack (BHA) is a kind of security hazard in which the malicious vehicle dewdrops controllers or data packets, turning an otherwise secure conduit or link into one that can be exploited. Accidents, deaths, and traffic jams can all result from dropped data packets on a VANET, so avoiding doing that is essential. Objective: To safeguard and enhance the general performance and security of the VANETs, a unique technique termed "Detection and Prevention of a BHA (DPBHA) is proposed in this study. Methodology: Detection and Prevention of a BHA (DPBHA) is proposed and used. Findings: An active threshold value is calculated, and a fake route request (RREQ) packet is generated as part of the proposed solution. The solution is tested in the NS2 simulator and compared to industry standards for performance and effectiveness. Novelty: The outcomes presented showed that the planned DPBHA outpaced the benchmark outlines by raising the PDR by 3.0%, increasing the throughput by 6.15%, decreasing the routing overhead by 3.69%, reducing the end-toend delay by 6.13%, and obtaining a maximum detection accuracy of 94.66%.