A Survey of Network Attacks on Cyber-Physical Systems

Cao, Liwei; Jiang, Xiaoning; Zhao, Yumei; Wang, Shouguang; You, Dan; Xu, Xianli

doi:10.1109/access.2020.2977423

Cited by 90 publications

(35 citation statements)

References 76 publications

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“…Although has been proven by experts that machine learning models can detect [3,5,9,10,13,20,29,33] most types of cyberattacks with high performances, the mechanics that affect accuracy are not usually analyzed and discussed. Also, building performant machine learning models require large datasets of labeled instances [16,30].…”

Section: Introductionmentioning

confidence: 99%

Feature Selection Improves Tree-based Classification for Wireless Intrusion Detection

Bhandari

Kukreja

Lazar

et al. 2020

Proceedings of the 3rd International Workshop on Systems and Network Telemetry and Analytics

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With the growth of 5G wireless technologies and IoT, it become urgent to develop robust network security systems, such as intrusions detection systems (IDS) to keep the networks secure. These IDS systems need to detect unauthorized access and attacks in real-time. However, most of the modern IDS are built based on complex machine learning models that are time-consuming to train. In this work, we propose a methodology using the SHapley Additive exPlanations (SHAP) in combination with tree-based classifiers. SHAP can be used to select consistent and small feature subsets to reduce the execution time and improve classification accuracy. We demonstrate the proposed approach with the Aegean Wi-Fi Intrusion Dataset (AWID) dataset in a series of multi-class classification experiments. Among the four classes ("normal", "injection", "flooding" and "impersonation"), it is well-known that the class impersonation is hard to be classified accurately. Tests show that we can use about 10% of the initial feature set without reducing the overall prediction accuracy. With this reduced set of features, the training time could be reduced as much as a factor of four, while slightly improving the discriminating ability to identify impersonation instances. This study suggests that by reducing the number of features, the classification algorithms are able to focus on key trends that differentiates the "attacks" classes from the "normal" class. Using a reduces subset of features improves IDS's accuracy and performance. Also, SHAP dependence plots capture the relationship between individual features and the classification decision.

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Section: Introductionmentioning

confidence: 99%

Feature Selection Improves Tree-based Classification for Wireless Intrusion Detection

Bhandari

Kukreja

Lazar

et al. 2020

Proceedings of the 3rd International Workshop on Systems and Network Telemetry and Analytics

View full text Add to dashboard Cite

show abstract

“…The 2 nd CPS threat factors threat the target: the CPS applications and their users or components [109]. The 3 rd factor of the CPS threats is the motive of the danger in which the CPS assailants have reason to make an attack, e.g., spying, cyberwar, or criminal [110]. The 4 th factor of the CPS threats is the threat vector, which can do one of four mechanisms for a successful attack, e.g., alteration, disruption, fabrication, and interception.…”

Section: A General Cps Threats Factorsmentioning

confidence: 99%

CPS Attacks Mitigation Approaches on Power Electronic Systems With Security Challenges for Smart Grid Applications: A Review

et al. 2021

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This paper presents an inclusive review of the cyber-physical (CP) attacks, vulnerabilities, mitigation approaches on the power electronics and the security challenges for the smart grid applications. With the rapid evolution of the physical systems in the power electronics applications for interfacing renewable energy sources that incorporate with cyber frameworks, the cyber threats have a critical impact on the smart grid performance. Due to the existence of electronic devices in the smart grid applications, which are interconnected through communication networks, these networks may be subjected to severe cyber-attacks by hackers. If this occurs, the digital controllers can be physically isolated from the control loop. Therefore, the cyber-physical systems (CPSs) in the power electronic systems employed in the smart grid need special treatment and security. In this paper, an overview of the power electronics systems security on the networked smart grid from the CP perception, as well as then emphases on prominent CP attack patterns with substantial influence on the power electronics components operation along with analogous defense solutions. Furthermore, appraisal of the CPS threats attacks mitigation approaches, and encounters along the smart grid applications are discussed. Finally, the paper concludes with upcoming trends and challenges in CP security in the smart grid applications.

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“…This work copes with threats that may arise in the communication channel. A survey about network attacks in CPS is presented in [8]. The key idea of the proposed method is to design a secure control system capable of detecting the injection of tampered data (known as deception attack).…”

Section: Introductionmentioning

confidence: 99%

On the Use of Fibonacci Sequences for Detecting Injection Attacks in Cyber Physical Systems

et al. 2021

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Cyber Physical Systems are characterized by a strong interaction among networking, sensing, and control functionalities. Moreover, the recent advent of Internet of Things extended their information sharing capability. However, the interaction between Internet and Cyber Physical Systems requires increased efforts for guaranteeing the security of connected systems. In the industrial field, the problem becomes more complex due to the need of protecting a large attack surface while guaranteeing system availability and realtime response to the detection of threats. In this contribution, we deal with the injection of tampered data into the communication channel with the aim of modifying the status of the physical system. To cope with this attack, we design a secure control system able to detect the injection of tampered data by coding the output of the measurement systems. The proposed approach is based on the use of permutation matrices, whose scheme varies upon a secret pattern obtained exploiting the Fibonacci p-sequences. The detection strategy is compliant with the time delay constraints typical of a Cyber Physical System. An analysis of the security performances of the proposed system is presented along with the experimental proof of its effectiveness.

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A Survey of Network Attacks on Cyber-Physical Systems

Cited by 90 publications

References 76 publications

Feature Selection Improves Tree-based Classification for Wireless Intrusion Detection

Feature Selection Improves Tree-based Classification for Wireless Intrusion Detection

CPS Attacks Mitigation Approaches on Power Electronic Systems With Security Challenges for Smart Grid Applications: A Review

On the Use of Fibonacci Sequences for Detecting Injection Attacks in Cyber Physical Systems

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