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., driver assistance functions, intrusion detection system, vehicle diagnostics, external device authentication during vehicle diagnostics, vehicle-to-grid and so on). The cybersecurity attacks targeting the global time result in false time, accuracy degradation, and denial of service as stated in IETF RFC 7384.

October 29-31, 2019 │ Novi, MI

If you are not able to attend WCX 2022 in-person, you will have the opportunity to join a selected number of live technical and executive discussions online that will advance your skill set in propulsion, connectivity security and safety as well as the business of technology.

SAE EDGE Research Reports provide examinations significant topics facing mobility industry today including Connected Automated Vehicle Technologies Electrification Advanced Manufacturing

If you are not able to attend WCX 2022 in-person, you will have the opportunity to join a selected number of live technical and executive discussions online that will advance your skill set in propulsion, connectivity security and safety as well as the business of technology.

SAE EDGE Research Reports provide examinations significant topics facing mobility industry today including Connected Automated Vehicle Technologies Electrification Advanced Manufacturing

October 29-31, 2019 │ Novi, MI

Count on SAE International®—the global leader in technical learning for mobility professionals—to deliver emerging research, consumer metrics, regulatory standards and the latest innovations to advance mobility at the WCX World Congress event.

SAE EDGE Research Reports provide examinations significant topics facing mobility industry today including Connected Automated Vehicle Technologies Electrification Advanced Manufacturing

October 29-31, 2019 │ Novi, MI

Abstract Testing and verifying the security of connected and autonomous vehicles (CAVs) under cyber-physical attacks is a critical challenge for ensuring their safety and reliability. Proposed in this article is a novel testing framework based on a model of computation that generates scenarios and attacks in a closed-loop manner, while measuring the safety of the unit under testing (UUT), using a verification vector. The framework was applied for testing the performance of two cooperative adaptive cruise control (CACC) controllers under false data injection (FDI) attacks. Serving as the baseline controller is one of a traditional design, while the proposed controller uses a resilient design that combines a model and learning-based algorithm to detect and mitigate FDI attacks in real-time.