Checking is Believing: Event-Aware Program Anomaly Detection in Cyber-Physical Systems

被引:21
作者
Cheng, Long [1 ]
Tian, Ke [2 ]
Yao, Danfeng [3 ]
Sha, Lui [4 ]
Beyah, Raheem A. [5 ]
机构
[1] Clemson Univ, Sch Comp, Clemson, SC 29634 USA
[2] Microsoft, Redmond, WA 98052 USA
[3] Virginia Tech, Dept Comp Sci, Blacksburg, VA 24061 USA
[4] Univ Illinois, Dept Comp Sci, Champaign, IL 61820 USA
[5] Georgia Tech, Sch Elect & Comp Engn, Atlanta, GA 30332 USA
基金
美国国家科学基金会;
关键词
Cyber-physical systems; data-oriented attacks; program anomaly detection; cyber-physical execution semantics; INTRUSION DETECTION; SAFETY;
D O I
10.1109/TDSC.2019.2906161
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Securing cyber-physical systems (CPS) against malicious attacks is of paramount importance because these attacks may cause irreparable damages to physical systems. Recent studies have revealed that control programs running on CPS devices suffer from both control-oriented attacks (e.g., code-injection or code-reuse attacks) and data-oriented attacks (e.g., non-control data attacks). Unfortunately, existing detection mechanisms are insufficient to detect runtime data-oriented exploits, due to the lack of runtime execution semantics checking. In this work, we propose Orpheus, a new security methodology for defending against data-oriented attacks by enforcing cyber-physical execution semantics. We first present a general method for reasoning cyber-physical execution semantics of a control program (i.e., causal dependencies between the physical context/event and program control flows), including the event identification and dependence analysis. As an instantiation of Orpheus, we then present a new program behavior model, i.e., the event-aware finite-state automaton (eFSA). eFSA takes advantage of the event-driven nature of CPS control programs and incorporates event checking in anomaly detection. It detects data-oriented exploits if a specific physical event is missing along with the corresponding event dependent state transition. We evaluate our prototype's performance by conducting case studies under data-oriented attacks. Results show that eFSA can successfully detect different runtime attacks. Our prototype on Raspberry Pi incurs a low overhead, taking 0.0001s for each state transition integrity checking, and 0.063s similar to 0.211s for the cyber-physical contextual consistency checking.
引用
收藏
页码:825 / 842
页数:18
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