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Fuzzy adaptive observer-based resilient formation control for heterogeneous multiple unmanned aerial vehicles with false data injection attacks and prescribed performance

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TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL 2023年第6期45卷 1021-1036页

作者： Han, Bing Jiang, Ju Yu, Chaojun Nanjing Univ Aeronaut & Astronaut Coll Automat Engn Nanjing 211106 Jiangsu Peoples R China

This paper addresses the resilient formation control problem for heterogeneous multiple unmanned aerial vehicles (multi-UAV) under false data injection (FDI) attacks and prescribed performance constraints. The case of both actuator and sensor attacks is considered simultaneously, and the multi-UAV can exchange the information through a directed communication network. A fuzzy adaptive observer (FAO) is first proposed to estimate the FDI attacks and the unmeasurable velocity information for each UAV. In order to transform the formation control of heterogeneous multi-UAV into a trajectory tracking control problem of individual UAVs, a bank of distributed estimators is designed to achieve the leader's states by only using local information among neighboring UAVs. Then, by incorporating a novel tracking error transform method and fractional-order sliding mode control technique, a resilient prescribed performance tracking controller without velocity measurements is constructed. Furthermore, it is proved that all signals of the closed-loop formation control systems are uniformly ultimately bounded (UUB) stable under FDI attacks. Finally, the simulation results are given to verify the effectiveness and superiority of the proposed control strategy.

关键词： Multiple unmanned aerial vehicles false data injection attacks resilient formation control prescribed performance control

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A Blended Active Detection Strategy for false data injection attacks in Cyber-Physical Systems

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IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS 2021年第1期8卷 168-176页

作者： Ghaderi, Mohsen Gheitasi, Kian Lucia, Walter Concordia Univ Dept Elect & Comp Engn Montreal PQ H3G 1M8 Canada Concordia Univ Concordia Inst Informat Syst Engn Montreal PQ H3G 1M8 Canada

In recent years, different solutions have been proposed to detect advanced stealthy cyber-attacks against networked control systems. In this article, we propose a blended detection scheme that properly leverages and combines two existing detection ideas, namely, watermarking and moving target. In particular, a watermarked signal and a nonlinear static auxiliary function are combined to both limit the attacker's disclosure resources and obtain an unidentifiable moving target. The proposed scheme is capable of detecting a broad class of false data injection attacks, including zero-dynamics, replay, and covert attacks. Moreover, it is shown that the proposed approach mitigates the drawbacks of standard moving target and watermarking defense strategies. Finally, an extensive simulation study is reported to contrast the proposed detector with recent competitor schemes and provide tangible evidence of the effectiveness of the proposed solution.

关键词： Anomaly detection cyber-physical systems false data injection attacks networked control systems

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Event-triggered consensus control for DC microgrids based on MKELM and state observer against false data injection attacks

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INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS 2024年第3期15卷 775-793页

作者： Xie, Zongkui Wu, Zhongqiang Yanshan Univ Key Lab Ind Comp Control Engn Hebei Prov Qinhuangdao 066004 Peoples R China

This paper proposes an event-triggered distributed control method based on state observer and multi-kernel extreme learning machine (MKELM) for direct current microgrid, which can suppress the false data injection attacks (FDIA) in system. Firstly, considering the problem that most of the methods have poor suppression capability for discrete attacks in sensor signals, an MKELM-based suppression method for sensor attack is proposed. MKELM is used to model the microgrid system, the output current estimated by MKELM is employed in the controller instead of the current value measured by sensors, thus avoiding the FDIA present in sensors. Secondly, an event-triggered state observer-based distributed secondary control method with H-& INFIN;consensus performance is designed for suppressing the FDIA in communication link. In the controller, a state variable is constructed by deriving the microgrid system expression as a first-order multi-agent system, and then a state observer is designed to observe the transmitted information for isolating and suppressing the attack signals. And it is proved theoretically that the proposed event-triggered controller can achieve H-& INFIN;consensus convergence. Finally, simulation analyses verify the effectiveness of the method for suppressing FDIA in DC microgrid system.

关键词： DC microgrids Event-triggered mechanism Extreme learning machine false data injection attacks State observer

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Observer-Based Asynchronous Event-Triggered Bipartite Consensus of Multiagent Systems Under false data injection attacks

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IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS 2023年第3期10卷 1603-1615页

作者： Wang, Zhengxin Shi, Sangli He, Wangli Xiao, Min Cao, Jinde Gorbachev, Sergey Nanjing Univ Posts & Telecommun Sch Sci Nanjing 210023 Peoples R China Nanjing Univ Posts & Telecommun Jiangsu Engn Lab IOT Intelligent Robots IOTRobot Nanjing 210023 Peoples R China East China Univ Sci & Technol Key Lab Smart Mfg Energy Chem Proc Minist Educ Shanghai 200237 Peoples R China Nanjing Univ Posts & Telecommun Sch Automat Nanjing 210023 Peoples R China Southeast Univ Sch Math Nanjing 210096 Peoples R China Southeast Univ Frontiers Sci Ctr Mobile Informat Commun & Secur Nanjing Peoples R China Purple Mt Labs Nanjing 211111 Peoples R China Yonsei Univ Yonsei Frontier Lab Seoul 03722 South Korea Natl Res Tomsk State Univ Dept Innovat Technol Tomsk 634050 Russia

This article investigates bipartite consensus of multiagent systems under unknown false data injection attacks. attacks are launched in the channels from the controller to the actuator. To compensate for the impact of attacks, an extended observer including the absolute output information is first constructed, and then an observer-based event-triggered controller is designed to save resources. Moreover, an observer-based fully asynchronous event-triggered controller is proposed. Sufficient criteria are deduced to guarantee bipartite consensus, and Zeno behavior is further ruled out. Finally, numerical examples are given to illustrate the effectiveness of the derived results.

关键词： Protocols Control systems Multi-agent systems Symmetric matrices Network systems Telecommunications Synchronization Absolute output information extended observer bipartite consensus false data injection attacks observer-based event-triggered controller

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Adaptive predefined-time secure consensus tracking control for nonlinear multiagent systems against unknown false data injection attacks

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JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS 2024年第18期361卷

作者： Wen, Luyao Niu, Ben Ji, Yulong Zhang, Baoyi Shandong Normal Univ Sch Informat Sci & Engn Jinan 250014 Peoples R China

This paper primarily investigates the adaptive predefined-time secure consensus tracking control problem for a class of nonlinear multiagent systems (MASs) against unknown false data injection (FDI) attacks and Bouc-Wen hysteresis. Firstly, by using the Nussbaum functions in the controller design, the conservative limitation that the attack weight's sign must be consistently positive can not only be relaxed, but also the unknown compound gains problem caused by FDI attacks and input hysteresis can be resolved. Furthermore, the adaptive laws are designed in the form of a new nonlinear differential equation such that the predefined-time stability can be realized. In addition, a feasible adaptive predefined-time secure consensus tracking control strategy is developed based on the backstepping framework and the fuzzy approximation technique. It is demonstrated that all the closed-loop signals are semiglobally uniformly predefined-time-bounded (SGUPTB) and the outputs of all followers eventually synchronously track the output of the leader within a predefined time. Conclusively, a simulation example for the MASs composed of multiple single-link manipulators is provided to testify the effectiveness of the proposed control strategy.

关键词： Nonlinear multiagent systems Consensus tracking control false data injection attacks Input hysteresis Predefined-time

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Security control of multi -agent systems under false data injection attacks

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NEUROCOMPUTING 2020年 404卷 240-246页

作者： Zuo, Zhiqiang Cao, Xiong Wang, Yijing Tianjin Univ Sch Elect & Informat Engn Tianjin Key Lab Proc Measurement & Control Tianjin 300072 Peoples R China

This paper studies the consensus problem of multi-agent systems (MASs) with false data injection (FDI) attacks and noises. Based on the graphical method and Kalman filter framework, distributed state estimators are designed for the agents to estimate the states of neighbors. A threshold comparison approach is proposed to obtain the secure states. Combining the state estimation approach with the threshold scheme, security mechanism is put forward to ensure the mean square consensus of MASs subject to FDI attacks. Finally, numerical simulations are provided to illustrate the theoretical results.

关键词： Multi-agent systems false data injection attacks State estimation Security control

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Hybrid GSW and DM based fully homomorphic encryption scheme for handling false data injection attacks under privacy preserving data aggregation in fog computing

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JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING 2020年第11期11卷 5217-5231页

作者： Amuthan, A. Sendhil, R. Pondicherry Engn Coll Dept Comp Sci & Engn Pondicherry India

In recent years, the area of fog computing is receiving maximum focus due to the potential improvements in the cloud computing field. Fog computing is capable of resolving issues that includes location awareness, inadequate mobility support and high latency in the cloud computing environment. The internet of things (IoT) comprises of a collection of IoT equipments connected to fog nodes in order to aid the cloud service center for storing and processed a portion of data in prior. This process of storing and processing greatly minimizes the pressure in data processing with enhanced service and real time quality. However, data modification attacks and false data injection attacks introduce significant challenges over the fog nodes during the event of data processing. In this paper, Hybrid GSW (Gentry, Sahai, and Waters) and DM (Ducas and Micciancio) based fully homomorphic encryption (HGSW-DM-FHE) scheme was proposed for handling false data injection attacks under privacy preserving data aggregation in fog computing. This proposed HGSW-DM-FHE scheme is highly fault tolerant, since the process of data aggregation from other devices is not influenced even when the fog devices fails in operation. In addition, the proposed HGSW-DM-FHE scheme is determined to be efficient and secure by preventing the data injected from legal IoT devices are unaltered and protected immaterial to the honesty and maliciousness of the cloud control center and fog nodes.

关键词： Fog computing false data injection attacks Fully homomorphic encryption Privacy preserving data aggregation Internet of things (IoT)

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Partial grid false data injection attacks against state estimation

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2019年 110卷 623-629页

作者： Margossian, Harag Sayed, Mohammad Ali Fawaz, Wissam Nakad, Zahi Lebanese Amer Univ Dept Elect & Comp Engn Byblos Lebanon

The addition of an external communication layer to the power system has left it vulnerable to cyberattacks. false data injection (FDI) can be used to manipulate measurements that are used to estimate the state of the power system. Decisions made based on a false evaluation can result in major disturbances in its operation. Recent studies show how, with full knowledge about the system, these types of attacks can be mounted without being detected. This paper shows how, with knowledge limited only to a specific section of the power system, it is still possible to carry out an undetectable attack. The process of performing the attack and a proof of its undetect-ability is explained in detail and then illustrated through a case study on the widely adopted IEEE 14 bus system. Last but not least, the paper proposes a method to identify a subset of available measurements to be considered for protection against cyberattacks. This would render the entire network or specific parts of it immune to these attacks.

关键词： State estimation false data injection attacks Power systems

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A Framework for Detecting false data injection attacks in Large-Scale Wireless Sensor Networks

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SENSORS 2024年第5期24卷 1643页

作者： Hu, Jiamin Yang, Xiaofan Yang, Lu-Xing Chongqing Univ Sch Big Data & Software Engn Chongqing 400044 Peoples R China Deakin Univ Coll Informat Technol Melbourne Vic 3125 Australia

false data injection attacks (FDIAs) on sensor networks involve injecting deceptive or malicious data into the sensor readings that cause decision-makers to make incorrect decisions, leading to serious consequences. With the ever-increasing volume of data in large-scale sensor networks, detecting FDIAs in large-scale sensor networks becomes more challenging. In this paper, we propose a framework for the distributed detection of FDIAs in large-scale sensor networks. By extracting the spatiotemporal correlation information from sensor data, the large-scale sensors are categorized into multiple correlation groups. Within each correlation group, an autoregressive integrated moving average (ARIMA) is built to learn the temporal correlation of cross-correlation, and a consistency criterion is established to identify abnormal sensor nodes. The effectiveness of the proposed detection framework is validated based on a real dataset from the U.S. smart grid and simulated under both the simple FDIA and the stealthy FDIA strategies.

关键词： large-scale sensor networks false data injection attacks detection framework distributed solution

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Unscented Kalman filtering for nonlinear systems with sensor saturation and randomly occurring false data injection attacks

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ASIAN JOURNAL OF CONTROL 2021年第2期23卷 871-881页

作者： Lu, Jiyong Wang, Weizhen Li, Li Guo, Yanping Hebei Univ Sci & Technol Sch Elect Engn Shijiazhuang Hebei Peoples R China Yanshan Univ Sch Elect Engn Qinhuangdao 066004 Hebei Peoples R China Hebei Univ Sci & Technol Sch Sci Shijiazhuang Hebei Peoples R China

In this paper, an unscented Kalman filtering problem is studied for a nonlinear system with sensor saturation and randomly occurring false data injection attacks. A random variable obeying the Bernoulli distribution is employed to characterize the phenomena of the randomly occurring false data injection attacks. The aim of this paper is to design a modified unscented Kalman filter by minimizing an upper bound of filtering error covariance. Furthermore, a sufficient condition is provided to ensure an exponentially bounded filtering error in the mean square sense. Numerical simulations are presented to illustrate the validity of the proposed filter.

关键词： false data injection attacks nonlinear system sensor saturation unscented Kalman filtering

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