Can We Trust Autonomous Cars? An Expert Panel Discussion on ADAS Cybersecurity

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Dell Technologies, Ward's Intelligence and the Fraunhofer Institute

About this talk

Cybersecurity threats are a reality for any industry, but not many have as severe potential consequences as the development of Advanced Driver Assistance Systems (ADAS) and future self-driving cars. While vehicles become software-defined, running on platform-standardized hardware chips, the potential threat landscape is expanding, with wide reaching workloads that span vehicle fleets, core datacenters and into the cloud. Cybersecurity needs to be a central consideration for ADAS and self-driving development workloads. Failure to account for this could lead to non-compliance with regulations such as UN/ECE WP.29, loss of consumer confidence and in the worst-case scenario, the loss of life. Join industry experts Dr.-Ing. Rasmus Adler, Autonomous Systems Program Manager, Fraunhofer Institute for Experimental Software Engineering; Steve Bell, Principal Analyst for Connectivity, Ward’s Intelligence; and Dr. Florian Baumann, Automotive Industry CTO, Dell Technologies; as they discuss how cybersecurity is impacting the industry. In this panel discussion, you will learn: • How digital ecosystems and value creation networks connect various stakeholders and how a distributed, cloud-based execution platform based on AI can comply with regulations. • What new concepts and infrastructures are required to design, develop and test secure software, codes and chips to ensure that Over-the-Air software updates will be available to fix detected security risks post-sale. • What kind of workloads need to be on-prem, what non-safety critical workloads can be deployed in the cloud, and how to set up a hybrid cloud environment that combines the value of both • Why AI-based cloud services that are key to autonomous technology must be trained with data sets that can contain a personal reference, without this being immediately apparent. When is 'legally secure' anonymization of data for development of AI functions available? Is it still possible in the age of big data?

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