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Conference Papers Year : 2022

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


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 the 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.
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hal-03641576 , version 1 (29-06-2022)



Nicolas Bellec, Guillaume Hiet, Simon Rokicki, Frédéric Tronel, Isabelle Puaut. RT-DFI: Optimizing Data-Flow Integrity for Real-Time Systems. ECRTS 2022 - 34th Euromicro Conference on Real-Time Systems, Jul 2022, Modène, Italy. pp.1-24, ⟨10.4230/LIPIcs.ECRTS.2022.18⟩. ⟨hal-03641576⟩
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