Title | Highly Available, Self-Defending, and Malicious Fault-Tolerant Systems for Automotive Cybersecurity |
Publication Type | Conference Paper |
Year of Publication | 2019 |
Authors | Liem, Clifford, Murdock, Dan, Williams, Andrew, Soukup, Martin |
Conference Name | 2019 IEEE 19th International Conference on Software Quality, Reliability and Security Companion (QRS-C) |
Keywords | automobiles, automotive cybersecurity, Automotive engineering, brand degradation, cars, cloud computing, composability, computer security, electronic features, Fault tolerance, Fault tolerant systems, fraud, highly available systems, integrity verification, intrusion tolerance, malicious attacks, malicious fault-tolerance, malicious fault-tolerant systems, Monitoring, pubcrawl, Resiliency, road safety, road-side equipment, Safety, security of data, self-defending techniques, self-defending technologies, self-healing systems, self-repair, single protection technique, smart phones, smartphones, software fault tolerance, system-level integrity, traffic engineering computing, warranty fraud |
Abstract | With the growing number of electronic features in cars and their connections to the cloud, smartphones, road-side equipment, and neighboring cars the need for effective cybersecurity is paramount. Beyond the concern of brand degradation, warranty fraud, and recalls, what keeps manufacturers up at night is the threat of malicious attacks which can affect the safety of vehicles on the road. Would any single protection technique provide the security needed over the long lifetime of a vehicle? We present a new methodology for automotive cybersecurity where the designs are made to withstand attacks in the future based on the concepts of high availability and malicious fault-tolerance through self-defending techniques. When a system has an intrusion, self-defending technologies work to contain the breach using integrity verification, self-healing, and fail-over techniques to keep the system running. |
DOI | 10.1109/QRS-C.2019.00018 |
Citation Key | liem_highly_2019 |