Data Logic Attack on Heavy-Duty Industrial Manipulators

Li, Lianpeng; Xie, Liang-Liang; Hao, Bing; Yang, Liusong; Hu, Tonghai; Wang, Zhiliang

doi:10.1109/access.2020.2966764

Cited by 5 publications

(2 citation statements)

References 37 publications

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“…As attacks against robotic arm systems are intensively studied, the current attacks may involve protocol attacks, sensor data attacks and control system attacks. For example, in [7], Li. et al performed a data logic attack on the EtherCAT communication protocol of a heavy-duty industrial robotic arm, mainly targeting the data packets between the control system and the actuator or between the sensor and the control system, by reordering, dropping or delaying the protocol packets to break the data logic of the communication protocol.…”

Section: Introductionmentioning

confidence: 99%

Research on a PSO-H-SVM-Based Intrusion Detection Method for Industrial Robotic Arms

2022

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The automation and intelligence of industrial manufacturing is the core of the fourth industrial revolution, and robotic arms and proprietary networked information systems are an integral part of this vision. However, with the benefits come risks that have been overlooked, and robotic arms have become a heavily attacked area. In order to improve the security of the robotic arm system, this paper proposes an intrusion detection method based on a state classification model. The closure operation process of the robotic arm is divided into five consecutive states, while a support vector machine based on the particle swarm optimization algorithm (PSO-H-SVM) classifies the operation state of the robotic arm. In the detection process, the classifier predicts the operation state of the robotic arm in real time, and the detection method determines whether the state transfer meets the logical requirements, and then determines whether the intrusion occurs. In addition, a response mechanism is proposed on the basis of the intrusion detection system to make protection measures for the robotic arm system. Finally, a physical experiment platform was built to test the intrusion detection method. The results showed that the classification accuracy of the PSO-H-SVM algorithm reached 96.02%, and the detection accuracy of the intrusion detection method reached 90%, which verified the effectiveness and reliability of the intrusion detection method.

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Section: Introductionmentioning

confidence: 99%

Research on a PSO-H-SVM-Based Intrusion Detection Method for Industrial Robotic Arms

2022

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“…The industrial control system can be remotely interacted with and communicated with cloud services [ 1 ], cyber-physical systems [ 2 ], or edge devices in a highly networked environment [ 3 ]. Cyber-attacks are increasingly becoming a threat to ICS; thus, their security is critical [ 4 , 5 ]. Once an essential piece of equipment experiences a safety incident, it causes a shutdown of the system and even causes casualties [ 6 ].…”

Section: Introductionmentioning

confidence: 99%

A Three-Stage Dynamic Assessment Framework for Industrial Control System Security Based on a Method of W-HMM

Wei

Chen

et al. 2022

Sensors

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Industrial control systems (ICS) are applied in many fields. Due to the development of cloud computing, artificial intelligence, and big data analysis inducing more cyberattacks, ICS always suffers from the risks. If the risks occur during system operations, corporate capital is endangered. It is crucial to assess the security of ICS dynamically. This paper proposes a dynamic assessment framework for industrial control system security (DAF-ICSS) based on machine learning and takes an industrial robot system as an example. The framework conducts security assessment from qualitative and quantitative perspectives, combining three assessment phases: static identification, dynamic monitoring, and security assessment. During the evaluation, we propose a weighted Hidden Markov Model (W-HMM) to dynamically establish the system’s security model with the algorithm of Baum–Welch. To verify the effectiveness of DAF-ICSS, we have compared it with two assessment methods to assess industrial robot security. The comparison result shows that the proposed DAF-ICSS can provide a more accurate assessment. The assessment reflects the system’s security state in a timely and intuitive manner. In addition, it can be used to analyze the security impact caused by the unknown types of ICS attacks since it infers the security state based on the explicit state of the system.

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A Study on Networked Industrial Robots in Smart Manufacturing: Vulnerabilities, Data Integrity Attacks and Countermeasures

Shao,

Xie,

et al. 2023

J Intell Robot Syst

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Data Logic Attack on Heavy-Duty Industrial Manipulators

Cited by 5 publications

References 37 publications

Research on a PSO-H-SVM-Based Intrusion Detection Method for Industrial Robotic Arms

Research on a PSO-H-SVM-Based Intrusion Detection Method for Industrial Robotic Arms

A Three-Stage Dynamic Assessment Framework for Industrial Control System Security Based on a Method of W-HMM

A Study on Networked Industrial Robots in Smart Manufacturing: Vulnerabilities, Data Integrity Attacks and Countermeasures

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