Security-Aware Modeling and Efficient Mapping for CAN-Based Real-Time Distributed Automotive Systems

Chung Wei Lin, Qi Zhu, Alberto Sangiovanni-Vincentelli

Research output: Contribution to journalArticle

20 Scopus citations

Abstract

Security has become a critical issue for automotive electronic systems. To protect against attacks, security mechanisms have to be applied, but the overhead of those mechanisms may impede system performance and cause violations of design constraints. To remedy this problem, we proposed an integrated mixed integer linear programming (MILP) formulation that is the first to address both security and safety constraints during system mapping for controller area network (CAN) based systems. However, its signal-based security constraints do not fully reflect real security requirements, and its objective function is to minimize functional path latencies rather than minimize security risk. Furthermore, its MILP-based approach has high computation complexity. In this work, we present a new formulation that defines path-based security constraints and minimizes security risk directly, and propose a new heuristic algorithm to solve the formulation efficiently. Experiments on an industrial example show that our new algorithm achieves comparable solution quality as the MILP-based approach with much better efficiency.

Original languageEnglish (US)
Article number6891169
Pages (from-to)11-14
Number of pages4
JournalIEEE Embedded Systems Letters
Volume7
Issue number1
DOIs
StatePublished - Mar 1 2015

Keywords

  • Automotive systems
  • cyber-physical systems
  • design space exploration
  • embedded systems
  • security

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science(all)

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