An Efficient Dynamic Solution for the Detection and Prevention of Black Hole Attack in VANETs

• Published in: Sensors (Basel, Switzerland) Vol. 22; no. 5; p. 1897
• Main Authors: Malik, Abdul, Khan, Muhammad Zahid, Faisal, Mohammad, Khan, Faheem, Seo, Jung-Taek
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 28.02.2022; MDPI
• Subjects: AODV; BHA; Black holes; Communication; Fatalities; Information sharing; Infrastructure; IoT; Network security; Traffic congestion; VANET; Vehicles; VANET; BHA; network security; AODV; IoT
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s22051897

Rapid and tremendous advances in wireless technology, miniaturization, and Internet of things (IoT) technology have brought significant development to vehicular ad hoc networks (VANETs). VANETs and IoT together play a vital role in the current intelligent transport system (ITS). However, a VANET is highly vulnerable to various security attacks due to its highly dynamic, decentralized, open-access medium, and protocol-design-related concerns. Regarding security concerns, a black hole attack (BHA) is one such threat in which the control or data packets are dropped by the malicious vehicle, converting a safe path/link into a compromised one. Dropping data packets has a severe impact on a VANET’s performance and security and may cause road fatalities, accidents, and traffic jams. In this study, a novel solution called detection and prevention of a BHA (DPBHA) is proposed to secure and improve the overall security and performance of the VANETs by detecting BHA at an early stage of the route discovery process. The proposed solution is based on calculating a dynamic threshold value and generating a forged route request (RREQ) packet. The solution is implemented and evaluated in the NS-2 simulator and its performance and efficacy are compared with the benchmark schemes. The results showed that the proposed DPBHA outperformed the benchmark schemes in terms of increasing the packet delivery ratio (PDR) by 3.0%, increasing throughput by 6.15%, reducing the routing overhead by 3.69%, decreasing the end-to-end delay by 6.13%, and achieving a maximum detection rate of 94.66%.