Opportunistic Data Flow Integrity for Real-time Cyber-physical Systems Using Worst Case Execution Time Reservation
Yujie Wang, Ao Li, Jinwen Wang, Sanjoy K. Baruah, Ning Zhang
摘要
With the proliferation of safety-critical real-time systems in our daily life, it is imperative that their security is protected to guarantee their functionalities. To this end, one of the most powerful modern security primitives is the enforcement of data flow integrity. However, the run-time overhead can be prohibitive for real-time cyber-physical systems. On the other hand, due to strong safety requirements on such real-time cyber-physical systems, platforms are often designed with enough reservation such that the system remains real-time even if it is experiencing the worst-case execution time. We conducted a measurement study on eight popular CPS systems and found the worst-case execution time is often at least five times the average run time. In this paper, we propose opportunistic data flow integrity, OP-DFI, that takes advantage of the system reservation to enforce data flow integrity to the CPS software. To avoid impacting the real-time property, OP-DFI tackles the challenge of slack estimation and run-time policy swapping to take advantage of the extra time in the system opportunistically. To ensure the security protection remains coherent, OP-DFI leverages in-line reference monitors and hardware-assisted features to perform dynamic fine-grained sandboxing. We evaluated OP-DFI on eight real-time CPS. With a worst-case execution time overhead of 2.7%, OP-DFI effectively performs DFI checking on 95.5% of all memory operations and 99.3% of safety-critical control-related memory operations on average.
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引用它的顶会 Paper6
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- PEARTS: Provable Execution in Real-Time Embedded SystemsAntonio Joia Neto, Norrathep Rattanavipanon, Ivan De Oliveira NunesS&P 2025
- SoK: On the Fragility of Memory Error Exploit MitigationsAdriaan Jacobs, Mahmoud Ammar, Stijn VolckaertUSENIX Security 2026
- ARM MTE Performance in PracticeTaehyun Noh, Yingchen Wang, Tal Garfinkel, Mahesh Madhav 等USENIX Security 2026
- ARTO: Efficient Execution Integrity Attestation for Real-Time Operation of Cyber-Physical SystemsRuizhe Zhao, Cong Sun, Zongzhen Li, Tiantian Wang 等USENIX Security 2026
它引用的顶会 Paper12
- Data-Oriented Programming: On the Expressiveness of Non-control Data AttacksHong Hu, Shweta Shinde, Sendroiu Adrian, Zheng Leong Chua 等S&P 2016 · 被引用 420 次
- Block Oriented Programming: Automating Data-Only AttacksKyriakos K. Ispoglou, Bader AlBassam, Trent Jaeger, Mathias PayerCCS 2018 · 被引用 143 次
- Enforcing Kernel Security Invariants with Data Flow IntegrityChengyu Song, Byoungyoung Lee, Kangjie Lu, William Harris 等NDSS 2016 · 被引用 141 次
- Origin-sensitive Control Flow IntegrityMustakimur Khandaker, Wenqing Liu, Abu Naser, Zhi Wang 等USENIX Security 2019 · 被引用 71 次
- RT-TEE: Real-time System Availability for Cyber-physical Systems using ARM TrustZoneJinwen Wang, Ao Li, Haoran Li, Chenyang Lu 等S&P 2022 · 被引用 69 次
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