ML-Driven Malware that Targets AV Safety

Saurabh Jha, Shengkun Cui, Subho Banerjee, James Cyriac, Timothy Tsai, Zbigniew Kalbarczyk, Ravishankar K. Iyer

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Ensuring the safety of autonomous vehicles (AVs) is critical for their mass deployment and public adoption. However, security attacks that violate safety constraints and cause accidents are a significant deterrent to achieving public trust in AVs, and that hinders a vendor's ability to deploy AVs. Creating a security hazard that results in a severe safety compromise (for example, an accident) is compelling from an attacker's perspective. In this paper, we introduce an attack model, a method to deploy the attack in the form of smart malware, and an experimental evaluation of its impact on production-grade autonomous driving software. We find that determining the time interval during which to launch the attack is{ critically} important for causing safety hazards (such as collisions) with a high degree of success. For example, the smart malware caused 33X more forced emergency braking than random attacks did, and accidents in 52.6% of the driving simulations.

Original languageEnglish (US)
Title of host publicationProceedings - 50th Annual IEEE/IFIP International Conference on Dependable Systems and Networks, DSN 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages113-124
Number of pages12
ISBN (Electronic)9781728158099
DOIs
StatePublished - Jun 2020
Event50th Annual IEEE/IFIP International Conference on Dependable Systems and Networks, DSN 2020 - Valencia, Spain
Duration: Jun 29 2020Jul 2 2020

Publication series

NameProceedings - 50th Annual IEEE/IFIP International Conference on Dependable Systems and Networks, DSN 2020

Conference

Conference50th Annual IEEE/IFIP International Conference on Dependable Systems and Networks, DSN 2020
CountrySpain
CityValencia
Period6/29/207/2/20

Keywords

  • Autonomous Vehicles
  • Safety
  • Security

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Hardware and Architecture
  • Information Systems
  • Information Systems and Management
  • Safety, Risk, Reliability and Quality

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