| Title | Security-Aware Malicious Event Detection using Multivariate Deep Regression Setup for Vehicular Ad hoc Network Aimed at Autonomous Transportation System |
| Publication Type | Conference Paper |
| Year of Publication | 2022 |
| Authors | Tariq, Usman |
| Conference Name | 2022 International Conference on Wireless Communications Signal Processing and Networking (WiSPNET) |
| Date Published | mar |
| Keywords | Ad Hoc Network Security, composability, malicious node, Metrics, Misbehavior detection, mobile nodes, pubcrawl, Real-time Systems, resilience, Resiliency, Scalability, security, Signal processing, Sybil attack, Transportation, Urban VANET, vehicular ad hoc networks, Wireless communication |
| Abstract | Vehicular Ad-hoc Networks (VANET) are capable of offering inter and intra-vehicle wireless communication among mobility aware computing systems. Nodes are linked by applying concepts of mobile ad hoc networks. VANET uses cases empower vehicles to link to the network to aggregate and process messages in real-time. The proposed paper addresses a security vulnerability known as Sybil attack, in which numerous fake nodes broadcast false data to the neighboring nodes. In VANET, mobile nodes continuously change their network topology and exchange location sensor-generated data in real time. The basis of the presented technique is source testing that permits the scalable identification of Sybil nodes, without necessitating any pre-configuration, which was conceptualized from a comparative analysis of preceding research in the literature. |
| DOI | 10.1109/WiSPNET54241.2022.9767185 |
| Citation Key | tariq_security-aware_2022 |
Security-Aware Malicious Event Detection using Multivariate Deep Regression Setup for Vehicular Ad hoc Network Aimed at Autonomous Transportation System