Presented at SAP Labs, France

1. 1
Connected cars - the security challenge:
Vehicles, Networks & Protocols
Ofer Rivlin
Product Security Lead @ Cyberark

2. 2

3. 3

4. 4

5. 5

6. 6

7. 7

8. 8

9. 9

10. 10
Mobile apps & Keyless entry

11. 11

12. 12

13. 13

14. 14
Radars & Vision

15. 15

16. 16

17. 17

18. 18
Computer Vision -
Slight alterations to an image, invisible to humans
can result in wildly different interpretations from a machine learning algorithm

19. 19
RADARs
▪ Accuracy (size & cost)

20. 20
RADARs
▪ Accuracy (size & cost)
▪ Interference (returning signals?)

21. 21
RADARs
▪ Accuracy (size & cost)
▪ Interference (returning signals?)
￭ Mitigation: Uniqueness by different frequency/encoding

22. 22
RADARs
▪ Accuracy (size & cost)
▪ Interference (returning signals?)
￭ Mitigation: Uniqueness by different frequency/encoding
▪ Privacy – Fingerprinting

23. 23
RADARs
▪ Accuracy (size & cost)
▪ Interference (returning signals?)
￭ Mitigation: Unique frequency/encoding
▪ Privacy – Fingerprinting
￭ Mitigation: Non-Unique properties

24. 24
RADARs
▪ Accuracy (size & cost)
▪ Interference (returning signals?)
￭ Mitigation: Unique frequency/encoding
▪ Privacy – Fingerprinting
￭ Mitigation: Non-Unique properties

25. 25
VANET/V2X
Current Security State
V2X Revocation Protocol

26. 26

27. 27
Cooperative Intelligent Transportation Systems
(cITS)
detect insider attacks
based on attacker behavior

28. 28
V2X Revocation Protocol
▪ Revocation of misbehaving vehicles in a V2X network
▪ Vehicles that perform harmful cyber security activities
▪ messages with spoofed positions, incorrect speeds, etc.

29. 29
Suggested Latest Solutions
OSR (Order for Self-Revocation)

30. 30
Identified issues with latest protocols

31. 31
Secure By Design using formal methods

32. 32
Connected Cars – Security in Future

33. 33
https://zerodium.com/program.html

34. 34

35. 35

36. 36

37. 37
Thank You!