Citation
Armin Wasicek. "Automotive Intrusion Detection". Talk or presentation, 11, February, 2016; Poster presented at the 2016 Berkeley EECS Annual Research Symposium.

Abstract
Cyber-Physical Intrusion Detection Systems are a novel type of IDS that are targeted to recognize physical manipulations of a control system. A control system's most important asset is the plant it is controlling. Manipulations of the controller might give an attacker benefits without proper authorization. In the automotive domain, for example, attacks like chip-tuning and powerboxing are transforming the engine control to gain more horsepower. Considering the new business model like function enabling in the automotive industry, these attacks do not only have a physical dimension, but also an economical aspect. In this presentation we will present a generic security framework and focus on intrusion detection as a means to detect manipulations in physical systems. Our approach leverages models derived from data to check plausibility and valid operation of a cyber-physical system.

Electronic downloads

• wasicek_autoids-poster_feb16.pdf · application/pdf · 1723 kbytes

• HTML

  Armin Wasicek. <a
  href="http://chess.eecs.berkeley.edu/pubs/1167.html"><i>Automotive
  Intrusion Detection</i></a>, Talk or
  presentation,  11, February, 2016; Poster presented at the
  <a
  href="https://www.terraswarm.org/conferences/16/bears/"
  >2016 Berkeley EECS Annual Research Symposium</a>.

• Plain text

  Armin Wasicek. "Automotive Intrusion Detection".
  Talk or presentation,  11, February, 2016; Poster presented
  at the <a
  href="https://www.terraswarm.org/conferences/16/bears/"
  >2016 Berkeley EECS Annual Research Symposium</a>.

• BibTeX

  @presentation{Wasicek16_AutomotiveIntrusionDetection,
      author = {Armin Wasicek},
      title = {Automotive Intrusion Detection},
      day = {11},
      month = {February},
      year = {2016},
      note = {Poster presented at the <a
                href="https://www.terraswarm.org/conferences/16/bears/"
                >2016 Berkeley EECS Annual Research Symposium</a>.},
      abstract = {Cyber-Physical Intrusion Detection Systems are a
                novel type of IDS that are targeted to recognize
                physical manipulations of a control system. A
                control system's most important asset is the plant
                it is controlling. Manipulations of the controller
                might give an attacker benefits without proper
                authorization. In the automotive domain, for
                example, attacks like chip-tuning and powerboxing
                are transforming the engine control to gain more
                horsepower. Considering the new business model
                like function enabling in the automotive industry,
                these attacks do not only have a physical
                dimension, but also an economical aspect. In this
                presentation we will present a generic security
                framework and focus on intrusion detection as a
                means to detect manipulations in physical systems.
                Our approach leverages models derived from data to
                check plausibility and valid operation of a
                cyber-physical system.},
      URL = {http://chess.eecs.berkeley.edu/pubs/1167.html}
  }
  

Posted by Armin Wasicek on 16 Feb 2016.
Groups: chess
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