# Connected Vehicles Security: A Lightweight Machine Learning Model to Detect VANET Attacks
## 3 Related Work  
A VANET's structure consists of three main components, OBUs, RSUs, and the trusted authority (TA) [22, 23]: (i) Vehicles are equipped with OBUs that facilitate communication between them using the dedicated short-range communication (DSRC) protocol. Message exchange and key requests are ongoing procedures, as long as cars are driven on the road. (ii) RSUs are wireless devices positioned all over the road to gather and process messages and perform intelligent traffic control operations. (iii) The TA is responsible for assigning system parameters and managing all network entities. Before being permitted to join the VANET, the RSUs and vehicles should be registered at the TA. The TA possesses the greatest storage and communication capacity. Although the RSUs and TA use protected channels for communication, the vehicles and RSUs use an open wireless medium to transmit messages. Consequently, wireless environments are subject to a variety of attacks that affect  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Attack Name** & **Authentication** & **Confidentiality** & **Privacy** & **Availability** & **Integrity** & **Authenticity** & **Non-Repudiation** \\ \hline Impersonation & & Yes & Yes & & Yes [20] & \\ \hline DoS & & & & Yes & Yes [20] & \\ \hline Masquerading & Yes & & & & & \\ \hline Wormhole/tunneling & Yes & Yes & & & & \\ \hline Bogus & & & & & & \\ information & & & & & & \\ \hline Black hole & & & & Yes & & \\ \hline Social attack & & & & Yes & & \\ \hline Malware & & & & Yes & & \\ \hline Man in the & & Yes & Yes & & Yes & \\ \hline Monitoring & & & Yes & & Yes & \\ attack & & & Yes & & Yes & \\ \hline Spamming & & & Yes & & & \\ \hline Illusion attack & & & Yes & Yes & & \\ \hline Timing attack & & & & Yes & & \\ \hline Sybil attack & Yes & Yes & & & Yes [20] & \\ \hline GPS spoofing & Yes & & & & \\ \hline Gray hole & & & Yes [20] & & & \\ \hline Hidden vehicle & Yes [20] & & & Yes [20] & \\ \hline Spoofing & & & & Yes [20] & \\ \hline Relay & & & Yes [20] & Yes [20] & Yes [20] & \\ \hline Position & & & & Yes [20] & & \\ falsification & & & & & \\ \hline \hline \end{tabular}
\end{table}
Table 2: VANET Attack Classifications Based on their Effects.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Physical Layer** & **Datalink Layer** & **Network Layer** & **Transport Layer** & **Application Layer** \\ \hline Impersonation attack & & Tunneling & DoS & \\ Jamming & Traffic analysis & Message tampering & Masquerading & \\ Free riding & Illusion attack & Black hole & & Reply \\ Replication & Greedy behavior & Jellyfish & GPS Spoofing & \\ Eavesdroping & & Gray hole & & DDoS \\ Man in the middle & & Wormhole & Spamming & \\ \hline \hline \end{tabular}
\end{table}
Table 3: Layer-Based Classification of VANET Attacks.  
VANET functionality and security. These attacks are increasing in terms of their ability to monitor, track, and modify the network traffic. Accordingly, multiple authentication protocols have been introduced to fortify VANET security; however, the majority of current authentication solutions that address security flaws result in significant computational and storage demands on OBUs [24].