A secure control framework for resource-limited adversaries

By André M. H. Teixeira, Iman Shames, Henrik Sandberg, Karl Henrik Johansson. at - Automatisierungstechnik, 2012

1,162 citations recorded by the source corpus.

Cyber-secure networked control is modeled, analyzed, and experimentally illustrated in this paper. An attack space defined by the adversary's model knowledge, disclosure, and disruption resources is introduced. Adversaries constrained by these resources are modeled for a networked control system architecture. It is shown that attack scenarios corresponding to denial-of-service, replay, zero-dynamics, and bias injection attacks on linear time-invariant systems can be analyzed using this framework. Furthermore, the attack policy for each scenario is described and the attack's impact is characterized using the concept of safe sets. An experimental setup based on a quadruple-tank process controlled over a wireless network is used to illustrate the attack scenarios, their consequences, and potential counter-measures.

Subfields: Artificial Intelligence, Control and Systems Engineering, Hardware and Architecture

View Paper: https://www.semanticscholar.org/paper/a6b4c9269bb9580b4a08f374a8ad448f8f8f68f2

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Citations in the corpus

Decentralized Adaptive Fuzzy Secure Control for Nonlinear Uncertain Interconnected Systems Against Intermittent DoS Attacks (2019, background): “Compared to these deception attacks, the DoS attacks, which attempt to block the information transmission between system devices or components, are easier to be launched for adversaries and more reachable in the attack space [10].”
Control-Theoretic Methods for Cyberphysical Security: Geometric Principles for Optimal Cross-Layer Resilient Control Systems (2015, background): “Finally, security issues of specific cyberphysical systems have received considerable attention, such as power networks [22]–[27], linear networks with misbehaving components [28]–[30], and water networks [31]–[33].”
Secure State Estimation and Control of Cyber-Physical Systems: A Survey (2021, background): “This confirms that attacks, having access to all measurement transmission channels, can be stealthy and bypass any anomaly detector [83].”
A systems and control perspective of CPS security (2019, background): “Also as mentioned above, DDD attacks have been discussed at length in [6], [38].”
Networked control systems: a survey of trends and techniques (2020, background): “In [21], the optimal control issue on DoS attacks under a maximum number of jamming actions within a prescribed control horizon is considered.”
Resilient control under Denial-of-Service: Robust design (2016, background): “There are varieties of attacks such as Denial-of-Service attacks, zero-dynamics attacks, bias injection attacks, to name a few [3].”
Limiting the Impact of Stealthy Attacks on Industrial Control Systems (2016, background): “Similarly, some properties of the physical system, such as systems vulnerable to zero-dynamics attacks [61], unbounded systems [62], and highly non-linear or chaotic systems [48], can also prevent us from detecting attacks.”
A Survey on Security Communication and Control for Smart Grids Under Malicious Cyber Attacks (2019, background): “More detailed information on modeling of cyber-physical security scenarios in network environments can be seen in [34] and [50]–[52].”
Event-Triggered Consensus Control for Multi-Agent Systems Against False Data-Injection Attacks (2019, background): “Generally, cyber attacks can be classiﬁed as denial-of-service (DoS) and deception attacks [31]–[33].”
Secure Cooperative Event-Triggered Control of Linear Multiagent Systems Under DoS Attacks (2020, background): “Gupta et al. [9], Zhang et al. [13], Teixeira et al. [14], Shisheh et al. [16], Cetinkaya et al. [17], De. Persis and Tesi [18], Chen et al. [19] studied the secure control against DoS attacks in a centralized setting.”
Distributed Resilient Observer-Based Fault-Tolerant Control for Heterogeneous Multiagent Systems Under Actuator Faults and DoS Attacks (2020, background): “Cyber attacks launched by opponents are usually carried out in two common ways: deception attacks (e.g., zero-dynamics attacks [12] and bias injection attacks [13]) and denial-of-service (DoS) attacks [14].”
Secure Control Systems: A Quantitative Risk Management Approach (2015, methodology): “The zero-dynamics attack signal and other scenarios were analyzed and performed in an experimental test bed of the QTP by [13].”
Resilient Event-Triggering $H_{\infty }$ Load Frequency Control for Multi-Area Power Systems With Energy-Limited DoS Attacks (2017, background): “In the literature, there are some nice results on the cyber-security under DoS and deception attacks [12], [14], [16].”