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RT-DFI: Optimizing Data-Flow Integrity for Real-Time Systems

Authors Nicolas Bellec , Guillaume Hiet , Simon Rokicki , Frederic Tronel , Isabelle Puaut

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Subject Classification

ACM Subject Classification
  • Software and its engineering → Real-time systems software
  • Security and privacy → Software and application security
Keywords
  • Real-time system
  • Software security
  • Data-flow integrity
  • Worst-case execution time

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Abstract

The emergence of Real-Time Systems with increased connections to their environment has led to a greater demand in security for these systems. Memory corruption attacks, which modify the memory to trigger unexpected executions, are a significant threat against applications written in low-level languages. Data-Flow Integrity (DFI) is a protection that verifies that only a trusted source has written any loaded data. The overhead of such a security mechanism remains a major issue that limits its adoption. This article presents RT-DFI, a new approach that optimizes Data-Flow Integrity to reduce its overhead on the Worst-Case Execution Time. We model the number and order of the checks and use an Integer Linear Programming solver to optimize the protection on the Worst-Case Execution Path. Our approach protects the program against many memory-corruption attacks, including Return-Oriented Programming and Data-Only attacks. Moreover, our experimental results show that our optimization reduces the overhead by 7% on average compared to a state-of-the-art implementation.

Cite As Get BibTex

Nicolas Bellec, Guillaume Hiet, Simon Rokicki, Frederic Tronel, and Isabelle Puaut. RT-DFI: Optimizing Data-Flow Integrity for Real-Time Systems. In 34th Euromicro Conference on Real-Time Systems (ECRTS 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 231, pp. 18:1-18:24, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022) https://doi.org/10.4230/LIPIcs.ECRTS.2022.18

Author Details

Nicolas Bellec
  • Univ Rennes, Inria, CNRS, IRISA, France
Guillaume Hiet
  • CentraleSupélec, Inria, Univ Rennes, CNRS, IRISA, France
Simon Rokicki
  • Univ Rennes, Inria, CNRS, IRISA, France
Frederic Tronel
  • CentraleSupélec, Inria, Univ Rennes, CNRS, IRISA, France
Isabelle Puaut
  • Univ Rennes, Inria, CNRS, IRISA, France

Acknowledgements

We want to warmly thank AbsInt for providing the aiT WCET estimator.

Supplementary Materials

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