With the rapid development of connected vehicles, people can get a better driving experience. However, the interconnection with the external network may bring growing accidents caused by cybersecurity vulnerabilities. As a result, automakers are paying more attention to cybersecurity and spending more cost on developing cybersecurity defense mechanisms. Threat analysis and risk assessment (TARA) is an efficient method to ensure the defense effect and greatly save costs in the early stage of vehicle development. It analyzes the threat of vehicle systems and determines the hierarchical defense and corresponding mitigations according to the potential threat to the system. This paper gives an overview of threat analysis and risk assessment in the automotive field. First, a novel classification of different TARA methods has been proposed. The existing methods have been analyzed and compared. Then, we have found some commonly used tools applied to TARA and compared their performance. After that, a concept named attack-defense mapping is proposed to figure out how to map the already found threats and vulnerabilities of the system to the appropriate mitigations. At last, the future development directions of TARA in the automotive domain have been discussed.

In modern automotive zonal electrical/electronic architectures, Time-Sensitive Networking (TSN) serves as the communication backbone, while Controller Area Network (CAN) operates as regional communication branches. The cross-domain communication requirements among CAN nodes distributed across different zones make CAN-TSN scheduling critically important. However, existing scheduling methods struggle to simultaneously meet CAN messages' real-time constraints and achieve efficient TSN bandwidth utilization, especially under high-load conditions with multiple CAN domains. To address these challenges, this paper introduces a comprehensive system model for CAN-TSN scheduling and, for the first time, establishes an aggregation theorem, providing a rigorous theoretical foundation for efficient CAN frame aggregation based on the AVTP protocol. Leveraging this theoretical result, a Constructive Heuristic Algorithm for AVTP-based CAN-TSN scheduling (CHAC) is proposed to produce initial high-quality scheduling solutions. Further optimization is conducted using a Hybrid Iterative Greedy Algorithm (HIGA), which integrates tabu list strategies and the Metropolis acceptance criterion to explore and refine solutions effectively. Simulation studies and prototype experiments conducted under heavy traffic scenarios demonstrate the effectiveness of the proposed methods. Compared to state-of-the-art approaches, the TSN link load is reduced by 41.7%, gateway CPU utilization decreases by 60.3%, and the CAN frame reception rate increases to 93.6%. These outcomes highlight the significant contribution of this research in advancing CAN-TSN scheduling performance, particularly under high-load scenarios, by achieving superior bandwidth utilization and robust real-time communication performance.

Driven by the rapid advancement of intelligence and connectivity, traditional distributed and signal-oriented automotive architectures are gradually being replaced by centralized, service-oriented architectures. In response to this transition, In-Vehicle Networks (IVNs) are expected to deliver high bandwidth, hard real-time performance, high reliability, and service-oriented capabilities. Data Distribution Service (DDS) and Time-Sensitive Networking (TSN) provide key technical support from the perspectives of service orientation and quality of service, respectively. Consequently, the integration of DDS and TSN has become a focal point in the field of IVNs. However, existing DDS message scheduling mechanisms cannot eliminate publishing time jitter, which prevents effective integration with deterministic scheduling mechanisms at the TSN layer, particularly the Time-Aware Shaper (TAS). To enable deterministic DDS communication in the DDS over TSN Architecture (DoTA), a Time-Triggered (TT) communication strategy based on message preemption and guard band mechanisms is proposed. This strategy is integrated into the flow controller of the DDS middleware. By scheduling a timed-event table, the publishing time of Time-Sensitive (TS) DDS messages is precisely controlled to align with the TAS mechanism. In addition, a schedulability analysis method is proposed to estimate the Worst-Case End-to-end Delay (WCED) of TS messages in DoTA. Experimental results from a physical testbed demonstrate that the proposed TT strategy can constrain the publishing time deviation of TS messages within 3 μs. When the TT strategy is jointly deployed with the TAS mechanism, both the end-to-end delay and jitter satisfy the requirements of safety-critical in-vehicle applications. Furthermore, the maximum deviation between the experimental results and the WCED estimated from the schedulability analysis is 15.4%. This indicates that the proposed method can effectively validate the feasibility of network designs and provide sufficient safety margins.