Sampling rate optimization for IEEE 802.11 wireless control systems

Kim, Dohwan; Won, Yuchang; Kim, Seunghyeon; Eun, Yongsoon; Park, Kyung‐Joon; Johansson, Karl Henrik

doi:10.1145/3302509.3311045

Cited by 12 publications

(3 citation statements)

References 19 publications

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“…The authors in [20] show that the proposed controller stabilizes the power system under bounded time-varying delays. The study [21] proposed a sampling rate optimization to mitigate the delay effect of an NCS with massive physical systems. Furthermore, study [21] formulated a physical instability by network delays as a network saturation problem and proposes a convex optimization problem considering control performance and network energies.…”

Section: B Controller Reconfiguration Against Cyber Attacksmentioning

confidence: 99%

Real-Time Controller Reconfiguration for Delay-Resilient Cyber-Physical Systems

Kim¹,

Lee

Park

2022

IEEE Access

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Networks on the cyber-physical systems (CPSs) configure feedback control loops between physical systems in the real world and control software in the cyber world. Malicious behaviors on the networks can increase network delays by exhausting limited network resources and security vulnerabilities to destabilize CPSs, which are entitled the network delay attack. In this paper, we focus on the problem of how to guarantee the stability of CPS under the network delay attack. We propose a real-time controller reconfiguration to ensure the resiliency of the physical systems against the network delay attack. Our controller reconfiguration consists of two algorithms: controller gain tuning and access point (AP) handover, which give a delay tolerance and an attack avoidance, respectively. Depending on the network delays, the computing system adopts one of these two algorithms and mitigates the physical impacts of the network delay attack. We validate that the proposed controller reconfiguration can ensure the resiliency of CPS against the network delay attack by implementing a testbed with wireless networks.INDEX TERMS Attack-resilient CPS, controller reconfiguration, cyber-physical systems, flooding attack.

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Section: B Controller Reconfiguration Against Cyber Attacksmentioning

confidence: 99%

Real-Time Controller Reconfiguration for Delay-Resilient Cyber-Physical Systems

Kim¹,

Lee

Park

2022

IEEE Access

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“…In the practical world, CPSs have integrated physical systems and software management in the cyber world, with networks responsible for information interchange (Kim et al, 2019). Technological developments in communications allow for low latency real-time communications, which enables the remote control of multiple physical systems and offers intelligent services to CPS users.…”

Section: Introductionmentioning

confidence: 99%

Advancements in Anomaly Detection: A Review of Machine Learning Applications in Cyber-Physical System Networks

Ahmed

2024

Preprint

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In the practical world, Cyber-Physical Systems have integrated physical systems and software management in the cyber-world, with networks responsible for information interchange. CPSs are key technologies for various industrial domains, including intelligent medical systems, transport systems, and smart grids. The advancements in cybersecurity have surpassed the rapid growth of CPS, with new security challenges and threat models that lack an integrated and cohesive framework. The review methodology includes the search strategy along with the inclusion and exclusion criteria of fifteen studies conducted in the past ten years. The studies specific to the relevant topic have been added, while the others have been excluded. According to the results, Machine Learning (ML) algorithms and systems can synthesize data. It is employed in cyber-physical security to alleviate concerns regarding the safety and reliability of the findings. ML offers a solution to complex problems, enhancing computer-human interaction and enabling problem-solving in areas where custom-built algorithms are impractical. A comprehensive overview of the application of ML across various domains, such as smart grids, smart vehicles, healthcare systems, and environmental monitoring, has been included. However, a few challenges are associated with implementing ML techniques in CPS networks, including feature selection complexity, model performance, deployment challenges, algorithm biases, model mismatches, and the need to foster a robust safety culture. Overall, integrating ML techniques with CPS networks holds promise for enhancing system safety, reliability, and security but requires ongoing refinement and adaptation to address existing limitations and emerging threats.

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“…C YBER-PHYSICAL systems (CPSs) are tightly integrated networked control systems, in which physical systems in the real world and control software in the cyber space are connected through networks [1]- [4]. While the network connectivity of CPS significantly enhances efficiency of complex industrial systems [5], this connectivity is vulnerable to malicious attacks that can make the physical systems unstable [6]- [8].…”

Section: Introductionmentioning

confidence: 99%

Stealthy Sensor Attack Detection and Real-Time Performance Recovery for Resilient CPS

Kim

Eun

Park

2021

IEEE Trans. Ind. Inf.

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Cyber-physical attacks exploit intrinsic natures of physical systems and can severely damage cyber-physical systems (CPSs) without being detected by the conventional anomaly detector. In this paper, based on software-defined networking, we propose a holistic resilient CPS framework that can detect, isolate, and recover from cyber-physical attacks in real-time. To show the effectiveness of the proposed framework, we focus on the pole-dynamics attack (PDA), a newly reported stealthy sensor attack that can make the physical system unstable. We develop an efficient detection algorithm for PDA and embed it into the proposed framework. By implementing a testbed, we validate that the proposed framework guarantees resilience of CPS against the PDA.

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Sampling rate optimization for IEEE 802.11 wireless control systems

Cited by 12 publications

References 19 publications

Real-Time Controller Reconfiguration for Delay-Resilient Cyber-Physical Systems

Real-Time Controller Reconfiguration for Delay-Resilient Cyber-Physical Systems

Advancements in Anomaly Detection: A Review of Machine Learning Applications in Cyber-Physical System Networks

Stealthy Sensor Attack Detection and Real-Time Performance Recovery for Resilient CPS

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