Worldwide,Vehicular Ad Hoc Networks (VANET) technology plays a vigorous role in providing the optimized expedition between the source and target. Modern technologies and Intelligent Transportation Systems (ITS) are associated significantly with providing wireless-based communications between vehicles (V2V). The Vehicular Ad Hoc Networks (VANETs) technology is used to increase the fidelity of interactions, effective traffic management, and driver's convince. In this smart technology, confidential information is transferred between autonomous vehicles. The autonomous vehicular technology is controlled with great flexibility but in the public network, the VANET attackers can create and transmit malicious messages to control the entire vehicle. Requirements on the security and privacy of VANET applications need to be addressed by developing a novel attack detection approach. A more reliable and highly effective approach is required to detect and avert DDoS attacks in smart VAVET applications. In this paper, we are reviewing the Distributed Denial of Service attacks (DDoS) and possible control mechanisms (Machine Learning, Cryptography, Data Mining) in the VANET applications for increasing the performance on hazard discovery. Future, our approach is aiming to implement in various real worldssmart vehicular applications for detecting the various attacks with high accuracy and effectiveness.