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Automotive Cybersecurity Challenges for Automated Vehicles: Jonathan Petit

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July 2016: Jonathan Petit, Principal Scientist at Security Innovation, discusses cybersecurity challenges for automated vehicles at the Automotive Vehicles Symposium.

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Automotive Cybersecurity Challenges for Automated Vehicles: Jonathan Petit

  1. 1. CYBERSECURITY CHALLENGES FOR AUTOMATEDVEHICLES Jonathan Petit jpetit@securityinnovation.com
  2. 2. J. Petit - AutomatedVehicles Symposium - July 20, 2016 2 Technical Challenges Governance Challenges
  3. 3. J. Petit - AutomatedVehicles Symposium - July 20, 2016 3 Technical Challenges Cameras Radars Sensor Processing Sensor Processing Sensor Fusion 3D Scanning Lidars Ultrasound sensors Sensor Processing Sensor Processing Action Engine Vehicle Controls - Brake/acc - Steering - etc. Visualization/Display Sub-system Raw data Object parameters - Time stamp - Dimensions - Position/velocity 3D Map Actions - Do nothing - Warn - Complement - Control Compressed data V2V / V2I comm. Sense Understand Act GPS IMS “Maps” a priori info Driver state Autonomous vehicle platform: a functional diagram Figure 1. A functional view of the data flow in an autonomous car’s sensing and control system.credit: F. Mujica. Scalable electronics driving autonomous vehicle technologies. Technical report, Autonomous Vehicles R&D, Kilby Labs, Texas Instruments, 2014.
  4. 4. J. Petit - AutomatedVehicles Symposium - July 20, 2016 3 Technical Challenges to-infrastructure (V2I) communications. On-board maps and associated cloud-based systems offer additional inputs via cellular communications. The outputs from all the sensor blocks are used to produce a 3D map of the environment around the vehicle. The map includes curbs and lane markers, vehicles, pedestrians, street signs and traffic lights, the car’s position in a larger map of the area and Finally, it is important to inform the driver visually about what the car “understands” of its environment. Displays that help the driver visualize the car and its environment can warn about road conditions and play a role in gaining acceptance of new technology. For instance, when drivers can see a 3D map that the vehicle uses for its operations, they will become more confident about the vehicle’s Cameras Radars Sensor Processing Sensor Processing Sensor Fusion 3D Scanning Lidars Ultrasound sensors Sensor Processing Sensor Processing Action Engine Vehicle Controls - Brake/acc - Steering - etc. Visualization/Display Sub-system Raw data Object parameters - Time stamp - Dimensions - Position/velocity 3D Map Actions - Do nothing - Warn - Complement - Control Compressed data V2V / V2I comm. Sense Understand Act GPS IMS “Maps” a priori info Driver state Autonomous vehicle platform: a functional diagram Figure 1. A functional view of the data flow in an autonomous car’s sensing and control system. credit: F. Mujica. Scalable electronics driving autonomous vehicle technologies. Technical report, Autonomous Vehicles R&D, Kilby Labs, Texas Instruments, 2014. On-Board Unit Data storage
  5. 5. J. Petit - AutomatedVehicles Symposium - July 20, 2016 Vehicle 3 Technical Challenges to-infrastructure (V2I) communications. On-board maps and associated cloud-based systems offer additional inputs via cellular communications. The outputs from all the sensor blocks are used to produce a 3D map of the environment around the vehicle. The map includes curbs and lane markers, vehicles, pedestrians, street signs and traffic lights, the car’s position in a larger map of the area and Finally, it is important to inform the driver visually about what the car “understands” of its environment. Displays that help the driver visualize the car and its environment can warn about road conditions and play a role in gaining acceptance of new technology. For instance, when drivers can see a 3D map that the vehicle uses for its operations, they will become more confident about the vehicle’s Cameras Radars Sensor Processing Sensor Processing Sensor Fusion 3D Scanning Lidars Ultrasound sensors Sensor Processing Sensor Processing Action Engine Vehicle Controls - Brake/acc - Steering - etc. Visualization/Display Sub-system Raw data Object parameters - Time stamp - Dimensions - Position/velocity 3D Map Actions - Do nothing - Warn - Complement - Control Compressed data V2V / V2I comm. Sense Understand Act GPS IMS “Maps” a priori info Driver state Autonomous vehicle platform: a functional diagram Figure 1. A functional view of the data flow in an autonomous car’s sensing and control system. credit: F. Mujica. Scalable electronics driving autonomous vehicle technologies. Technical report, Autonomous Vehicles R&D, Kilby Labs, Texas Instruments, 2014. Cloud services On-Board Unit Data storage
  6. 6. J. Petit - AutomatedVehicles Symposium - July 20, 2016 Vehicle 3 Technical Challenges to-infrastructure (V2I) communications. On-board maps and associated cloud-based systems offer additional inputs via cellular communications. The outputs from all the sensor blocks are used to produce a 3D map of the environment around the vehicle. The map includes curbs and lane markers, vehicles, pedestrians, street signs and traffic lights, the car’s position in a larger map of the area and Finally, it is important to inform the driver visually about what the car “understands” of its environment. Displays that help the driver visualize the car and its environment can warn about road conditions and play a role in gaining acceptance of new technology. For instance, when drivers can see a 3D map that the vehicle uses for its operations, they will become more confident about the vehicle’s Cameras Radars Sensor Processing Sensor Processing Sensor Fusion 3D Scanning Lidars Ultrasound sensors Sensor Processing Sensor Processing Action Engine Vehicle Controls - Brake/acc - Steering - etc. Visualization/Display Sub-system Raw data Object parameters - Time stamp - Dimensions - Position/velocity 3D Map Actions - Do nothing - Warn - Complement - Control Compressed data V2V / V2I comm. Sense Understand Act GPS IMS “Maps” a priori info Driver state Autonomous vehicle platform: a functional diagram Figure 1. A functional view of the data flow in an autonomous car’s sensing and control system. credit: F. Mujica. Scalable electronics driving autonomous vehicle technologies. Technical report, Autonomous Vehicles R&D, Kilby Labs, Texas Instruments, 2014. Cloud services On-Board Unit Data storage Infrastructure
  7. 7. J. Petit - AutomatedVehicles Symposium - July 20, 2016 Vehicle 3 Technical Challenges to-infrastructure (V2I) communications. On-board maps and associated cloud-based systems offer additional inputs via cellular communications. The outputs from all the sensor blocks are used to produce a 3D map of the environment around the vehicle. The map includes curbs and lane markers, vehicles, pedestrians, street signs and traffic lights, the car’s position in a larger map of the area and Finally, it is important to inform the driver visually about what the car “understands” of its environment. Displays that help the driver visualize the car and its environment can warn about road conditions and play a role in gaining acceptance of new technology. For instance, when drivers can see a 3D map that the vehicle uses for its operations, they will become more confident about the vehicle’s Cameras Radars Sensor Processing Sensor Processing Sensor Fusion 3D Scanning Lidars Ultrasound sensors Sensor Processing Sensor Processing Action Engine Vehicle Controls - Brake/acc - Steering - etc. Visualization/Display Sub-system Raw data Object parameters - Time stamp - Dimensions - Position/velocity 3D Map Actions - Do nothing - Warn - Complement - Control Compressed data V2V / V2I comm. Sense Understand Act GPS IMS “Maps” a priori info Driver state Autonomous vehicle platform: a functional diagram Figure 1. A functional view of the data flow in an autonomous car’s sensing and control system. credit: F. Mujica. Scalable electronics driving autonomous vehicle technologies. Technical report, Autonomous Vehicles R&D, Kilby Labs, Texas Instruments, 2014. Cloud services On-Board Unit Data storage Infrastructure Constraints • Cost (money) • Computation overhead • Space • Energy • Communication overhead
  8. 8. J. Petit - AutomatedVehicles Symposium - July 20, 2016 Vehicle 3 Technical Challenges to-infrastructure (V2I) communications. On-board maps and associated cloud-based systems offer additional inputs via cellular communications. The outputs from all the sensor blocks are used to produce a 3D map of the environment around the vehicle. The map includes curbs and lane markers, vehicles, pedestrians, street signs and traffic lights, the car’s position in a larger map of the area and Finally, it is important to inform the driver visually about what the car “understands” of its environment. Displays that help the driver visualize the car and its environment can warn about road conditions and play a role in gaining acceptance of new technology. For instance, when drivers can see a 3D map that the vehicle uses for its operations, they will become more confident about the vehicle’s Cameras Radars Sensor Processing Sensor Processing Sensor Fusion 3D Scanning Lidars Ultrasound sensors Sensor Processing Sensor Processing Action Engine Vehicle Controls - Brake/acc - Steering - etc. Visualization/Display Sub-system Raw data Object parameters - Time stamp - Dimensions - Position/velocity 3D Map Actions - Do nothing - Warn - Complement - Control Compressed data V2V / V2I comm. Sense Understand Act GPS IMS “Maps” a priori info Driver state Autonomous vehicle platform: a functional diagram Figure 1. A functional view of the data flow in an autonomous car’s sensing and control system. credit: F. Mujica. Scalable electronics driving autonomous vehicle technologies. Technical report, Autonomous Vehicles R&D, Kilby Labs, Texas Instruments, 2014. Cloud services On-Board Unit Data storage Challenges • HW security • SW security • OS security • Network security • Privacy Infrastructure Constraints • Cost (money) • Computation overhead • Space • Energy • Communication overhead
  9. 9. J. Petit - AutomatedVehicles Symposium - July 20, 2016 4 Technical Challenges Cameras Radars Sensor Processing Sensor Processing Sensor Fusion 3D Scanning Lidars Ultrasound sensors Sensor Processing Sensor Processing Action Engine Vehicle Controls - Brake/acc - Steering - etc. Visualization/Display Sub-system Raw data Object parameters - Time stamp - Dimensions - Position/velocity 3D Map Actions - Do nothing - Warn - Complement - Control Compressed data V2V / V2I comm. Sense Understand Act GPS IMS “Maps” a priori info Driver state Autonomous vehicle platform: a functional diagram Figure 1. A functional view of the data flow in an autonomous car’s sensing and control system.credit: F. Mujica. Scalable electronics driving autonomous vehicle technologies. Technical report, Autonomous Vehicles R&D, Kilby Labs, Texas Instruments, 2014. Cloud services Data storage Challenges • Pen-testing: assess security level / “score” • Protection: learn from military applications • Software/Firmware OTA update is critical • Can the sensors play an active role in the defense system?
  10. 10. J. Petit - AutomatedVehicles Symposium - July 20, 2016 5 Technical Challenges Cameras Radars Sensor Processing Sensor Processing Sensor Fusion 3D Scanning Lidars Ultrasound sensors Sensor Processing Sensor Processing Action Engine Vehicle Controls - Brake/acc - Steering - etc. Visualization/Display Sub-system Raw data Object parameters - Time stamp - Dimensions - Position/velocity 3D Map Actions - Do nothing - Warn - Complement - Control Compressed data V2V / V2I comm. Sense Understand Act GPS IMS “Maps” a priori info Driver state Autonomous vehicle platform: a functional diagram Figure 1. A functional view of the data flow in an autonomous car’s sensing and control system.credit: F. Mujica. Scalable electronics driving autonomous vehicle technologies. Technical report, Autonomous Vehicles R&D, Kilby Labs, Texas Instruments, 2014. Cloud services Data storage • Processing: filtering, normalization • Sometimes integrated to the sensor itself, otherwise data sent on the bus Challenges • HW-based security, host-based security with minimal overhead • Side-channel protection • Middleware security • Sensor authentication • In-vehicle network security
  11. 11. J. Petit - AutomatedVehicles Symposium - July 20, 2016 6 Technical Challenges Cameras Radars Sensor Processing Sensor Processing Sensor Fusion 3D Scanning Lidars Ultrasound sensors Sensor Processing Sensor Processing Action Engine Vehicle Controls - Brake/acc - Steering - etc. Visualization/Display Sub-system Raw data Object parameters - Time stamp - Dimensions - Position/velocity 3D Map Actions - Do nothing - Warn - Complement - Control Compressed data V2V / V2I comm. Sense Understand Act GPS IMS “Maps” a priori info Driver state Autonomous vehicle platform: a functional diagram Figure 1. A functional view of the data flow in an autonomous car’s sensing and control system.credit: F. Mujica. Scalable electronics driving autonomous vehicle technologies. Technical report, Autonomous Vehicles R&D, Kilby Labs, Texas Instruments, 2014. Cloud services Data storage Challenges • Often performed on fast CPU/GPU g HW security • Proposal: use “sensor security score” • How to harden adversarial input • How to differentiate attacks from faulty sensor? • How to obfuscate “weights”?
  12. 12. J. Petit - AutomatedVehicles Symposium - July 20, 2016 7 Technical Challenges Cameras Radars Sensor Processing Sensor Processing Sensor Fusion 3D Scanning Lidars Ultrasound sensors Sensor Processing Sensor Processing Action Engine Vehicle Controls - Brake/acc - Steering - etc. Visualization/Display Sub-system Raw data Object parameters - Time stamp - Dimensions - Position/velocity 3D Map Actions - Do nothing - Warn - Complement - Control Compressed data V2V / V2I comm. Sense Understand Act GPS IMS “Maps” a priori info Driver state Autonomous vehicle platform: a functional diagram Figure 1. A functional view of the data flow in an autonomous car’s sensing and control system. Cloud services credit: F. Mujica. Scalable electronics driving autonomous vehicle technologies. Technical report, Autonomous Vehicles R&D, Kilby Labs, Texas Instruments, 2014. Data storage External data • V2X • Maps • Cloud service Challenges • How much trust in external data? • Consensus inV2X network • Maps integrity and freshness • Secure cloud services
  13. 13. J. Petit - AutomatedVehicles Symposium - July 20, 2016 8 Technical Challenges Cameras Radars Sensor Processing Sensor Processing Sensor Fusion 3D Scanning Lidars Ultrasound sensors Sensor Processing Sensor Processing Action Engine Vehicle Controls - Brake/acc - Steering - etc. Visualization/Display Sub-system Raw data Object parameters - Time stamp - Dimensions - Position/velocity 3D Map Actions - Do nothing - Warn - Complement - Control Compressed data V2V / V2I comm. Sense Understand Act GPS IMS “Maps” a priori info Driver state Autonomous vehicle platform: a functional diagram Figure 1. A functional view of the data flow in an autonomous car’s sensing and control system. Cloud services credit: F. Mujica. Scalable electronics driving autonomous vehicle technologies. Technical report, Autonomous Vehicles R&D, Kilby Labs, Texas Instruments, 2014. Data storage Challenges • Decide what is best for the ego vehicle and the community (game theory) • Build a context-aware misbehavior engine (prediction, detection, reaction)
  14. 14. J. Petit - AutomatedVehicles Symposium - July 20, 2016 9 Technical Challenges Governance Challenges
  15. 15. J. Petit - AutomatedVehicles Symposium - July 20, 2016 10 Governance Challenges Encourage security by design (upgradability, crypto- agility), security testing (C/I/A analysis, security rating) Data ownership will affect privacy and security Forensicsability Role of road operators
  16. 16. J. Petit - AutomatedVehicles Symposium - July 20, 2016 11 Cameras Radars Sensor Processing Sensor Processing Sensor Fusion 3D Scanning Lidars Ultrasound sensors Sensor Processing Sensor Processing Action Engine Vehicle Controls - Brake/acc - Steering - etc. Visualization/Display Sub-system Raw data Object parameters - Time stamp - Dimensions - Position/velocity 3D Map Actions - Do nothing - Warn - Complement - Control Compressed data V2V / V2I comm. Sense Understand Act GPS IMS “Maps” a priori info Driver state Autonomous vehicle platform: a functional diagram Figure 1. A functional view of the data flow in an autonomous car’s sensing and control system. credit: F. Mujica. Scalable electronics driving autonomous vehicle technologies. Technical report, Autonomous Vehicles R&D, Kilby Labs, Texas Instruments, 2014. Cloud services 1. Pen-testing sensors and harden them 2. HW/Host- based security 3. Use “security level” as weight 4. Secure external (contextual) data 5. Misbehavior Detection
  17. 17. J. Petit - AutomatedVehicles Symposium - July 20, 2016 11 Cameras Radars Sensor Processing Sensor Processing Sensor Fusion 3D Scanning Lidars Ultrasound sensors Sensor Processing Sensor Processing Action Engine Vehicle Controls - Brake/acc - Steering - etc. Visualization/Display Sub-system Raw data Object parameters - Time stamp - Dimensions - Position/velocity 3D Map Actions - Do nothing - Warn - Complement - Control Compressed data V2V / V2I comm. Sense Understand Act GPS IMS “Maps” a priori info Driver state credit: F. Mujica. Scalable electronics driving autonomous vehicle technologies. Technical report, Autonomous Vehicles R&D, Kilby Labs, Texas Instruments, 2014. Cloud services 1. Pen-testing sensors and harden them 2. HW/Host- based security 3. Use “security level” as weight 4. Secure external (contextual) data 5. Misbehavior Detection Plan for Actions 1. Organize workshops with subject matter experts to establish cybersecurity guidelines for AV 2. Address technical challenges: HW, SW, system, network, privacy AND build a full automation system simulator (open source) 3. Address governance challenges: policies, forensics, data ownership, data sharing, security rating
  18. 18. Questions & Answers Jonathan Petit jpetit@securityinnovation.com For more info, check my ESCAR US 2016 presentation and publications list! Security Innovation Automotive Offerings: • Aerolink Security forVehicles • AutomotiveTraining Courses • Automotive Consulting Learn more about our automotive expertise!

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