Modeling Data Security and Privacy Threats for VANET using STRIDE and LINDDUN

Vehicular Ad Hoc Networks (VANETs) represent an innovative technology with the potential to revolutionize road safety, traffic management, and vehicular communication. Nevertheless, addressing substantial security concerns to ensure privacy and data integrity within the network is imperative for successfully deploying VANETs. This study conducts a comprehensive analysis of assets/threats target identification, threat modeling, and the development of mitigation strategies for the VANET environment using qualitative methods. We initiate the process by meticulously identifying and categorizing the assets vital to the operations of VANETs. These assets encompass various components based on the Data Flow Diagram (DFD) elements. A thorough understanding of these assets is crucial for assessing the security landscape in VANETs. Subsequently, we employ the STRIDE and LINDDUN threat modeling methodology to identify potential data security and privacy threats. We have identified 11 assets/threat targets and 34 distinct threats and then proposed 11 customized mitigation strategies for VANETs.