Trust-based distributed Kalman filtering for target tracking under malicious cyber attacks

Chen, Liang; Wen, Fuxi; Wang, Zhongmin

doi:10.1016/j.inffus.2018.04.002

Cited by 55 publications

(36 citation statements)

References 57 publications

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“…A distributed filter owning the capabilities of attack detection and state estimation is designed and tested via the wide-area monitoring of a power network in [146], where a hybrid Bernoulli random set is introduced to describe the joint information on the attack presence or no. Different from distributed filtering algorithms in the mean square sense [147], the paradigm of Kullback-Leibler fusion is utilized to handle the challenge from probability density function. It should be pointed out that the obtained algorithm only has limited robustness to attacks arising from the assumption on attack intensity.…”

Section: Distributed Security Control and Filteringmentioning

confidence: 99%

A Survey on Model-Based Distributed Control and Filtering for Industrial Cyber-Physical Systems

Ding

Han

Wang

et al. 2019

IEEE Trans. Ind. Inf.

436

124

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Industrial cyber-physical systems (CPSs) are largescale, geographically dispersed and life-critical systems, in which lots of sensors and actuators are embedded and networked together to facilitate real-time monitoring and closed-loop control. Their intrinsic features in geographic space and resources put forward to urgent requirements of reliability and scalability for designed filtering or control schemes. This paper presents a review of the state-of-the-art of distributed filtering and control of industrial CPSs described by differential dynamics models. Special attention is paid to sensor networks, manipulators and power systems. For real-time monitoring, some typical Kalmanbased distributed algorithms are summarized and their performances on calculation burden, communication burden as well as scalability are discussed in depth. Then, the characteristics of non-Kalman cases are further disclosed in light of constructed filter structures. Furthermore, the latest development is surveyed for distributed cooperative control of mobile manipulators and distributed model predictive control in industrial automation systems. By resorting to droop characteristics, representative distributed control strategies classified by controller structures are systematically summarized for power systems with the requirements of power sharing, and voltage and frequency regulation. In addition, distributed security control of industrial CPSs is reviewed when cyber-attacks are taken into consideration. Finally, some challenges are raised to guide the future research. Index Terms-Industrial cyber-physical systems; distributed filtering; distributed control; power schedule; droop characteristics. I. INDUSTRIAL CYBER-PHYSICAL SYSTEMS A cyber-physical system (CPS), a fast-growing research area, is a highly integrated system of physical components involving sensors, actuators and various equipments, as well as cyber possessing ubiquitous computation and efficient communication. From the engineering point of view, CPSs are considered as the most promising industrial systems including transportation networks, energy systems, water/gas distribution networks, and unmanned factories. For example, multiple industrial robots with an inertial navigation device or various sensors are programmed for the movement along a programmed trajectory to cooperatively complete production tasks [1], [2]. The main advantage of these systems is that the tight

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Section: Distributed Security Control and Filteringmentioning

confidence: 99%

A Survey on Model-Based Distributed Control and Filtering for Industrial Cyber-Physical Systems

Ding

Han

Wang

et al. 2019

IEEE Trans. Ind. Inf.

436

124

View full text Add to dashboard Cite

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“…Also in telecommunications and mobile networks, cyber-attacks can directly inject false data in the network, spread malware, send spam, or collect information for illegal purposes [169]. Self-organised networks [170,171] and virtual network functions [172,173] aid to get an early detection and better mitigation of cyber-attacks in mobile networks [174,175].…”

Section: Agent-based Complex Networkmentioning

confidence: 99%

Multi-Agent Systems and Complex Networks: Review and Applications in Systems Engineering

et al. 2020

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Systems engineering is an ubiquitous discipline of Engineering overlapping industrial, chemical, mechanical, manufacturing, control, software, electrical, and civil engineering. It provides tools for dealing with the complexity and dynamics related to the optimisation of physical, natural, and virtual systems management. This paper presents a review of how multi-agent systems and complex networks theory are brought together to address systems engineering and management problems. The review also encompasses current and future research directions both for theoretical fundamentals and applications in the industry. This is made by considering trends such as mesoscale, multiscale, and multilayer networks along with the state-of-art analysis on network dynamics and intelligent networks. Critical and smart infrastructure, manufacturing processes, and supply chain networks are instances of research topics for which this literature review is highly relevant.Processes 2020, 8, 312 2 of 29 in a telecommunication system network, nodes (e.g., routers and switches) may suffer over time a degradation in their properties that may lead them to diminish their performance. However, just the daily variation on traffic demand also has an impact on such nodes performance. Unexpected, external intervention such as cyber-attacks or extreme weather conditions may affect the properties, even the topology of a telecommunication system.Intelligent distributed systems are capable of modelling how different parts of the network might work individually and collectively [10]. Ultimately, this is used as support for any decision-making system aiming to achieve better overall system functioning and its consequent performance. Intelligent distributed systems encompass autonomous learning units that can be associated with the nodes of a complex network. These intelligent network nodes are able to act independently and also interact with other nodes to pursue both individual (local) and general system-level targets. The necessary communication between individuals can be represented by links of the complex network connecting their nodes. It is natural to understand such nodes as intelligent agents within a MAS framework. Each agent separately obeying simple rules but working together with other agents makes it possible to approach complex engineering challenges. Intelligent distributed systems have been proposed in a broad range of engineered complex systems [11,12]. Precisely, the review proposed herein focuses only on engineered systems and manufacturing processes, given the wide spectrum of the approached topic. Out of this review fall, then, topics related to social systems analysis such as migration models [13,14] or online social media [15,16]. Similarly, natural systems are out of this review scope. This is the case of computational chemistry [17,18], biology [19,20], and metabolic networks [21,22].Automatic optimisation and control in an engineering system is associated with a near real-time data acquisition and an optimal decision-making. Th...

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“…More recently, surveys on deception attacks began to appear, see [34][35][36][37][38][39]. For instance, in [34], the most general model of sensor attack resilient has been proposed, which can allow any signal to be injected through the compromised sensor.…”

Section: Related Workmentioning

confidence: 99%

“…In [35,37,38], the distributed state estimator, which was used to defend against false data injection attacks over sensor networks, has been embedded with event-triggering transmission scheme. Based on clustering technology, which can remove bad data and/or inaccurate estimates, a distributed Kalman filtering approach with trust-based dynamic combination strategy has been proposed in [39] to enhance the robustness against cyber attacks.…”

Section: Related Workmentioning

confidence: 99%

“…It should be noted that, for the problem solved in this paper, (i) External interference in sensor networks does not require known statistical properties, and (ii) The order of the distributed filter is controlled by a parameter, and distributed full-order and distributed reduced-order filters can be obtained for each node of the sensor networks, respectively. Unfortunately, the first factor prevents existing methods (Kalman filtering, extended Kalman filtering, see [11,14,19,39]) from being applied to distributed state estimation problems for sensor networked systems with unknown interference. On the other hand, the second factor is ignored by many existing H ∞ methods, see [16,38,42,43], which often focus on designing distributed full-order filters over WSNs.…”

Section: Simulation Examplementioning

confidence: 99%

See 1 more Smart Citation

Distributed Robust Filtering for Wireless Sensor Networks with Markov Switching Topologies and Deception Attacks

Zhu

Liu

Wen

et al. 2020

Sensors

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This paper is concerned with the distributed full- and reduced-order l 2 - l ∞ state estimation issue for a class of discrete time-invariant systems subjected to both randomly occurring switching topologies and deception attacks over wireless sensor networks. Firstly, a switching topology model is proposed which uses homogeneous Markov chain to reflect the change of filtering networks communication modes. Then, the sector-bound deception attacks among the communication channels are taken into consideration, which could better characterize the filtering network communication security. Additionally, a random variable obeying the Bernoulli distribution is used to describe the phenomenon of the randomly occurring deception attacks. Furthermore, through an adjustable parameter E, we can obtain full- and reduced-order l 2 - l ∞ state estimator over sensor networks, respectively. Sufficient conditions are established for the solvability of the addressed switching topology-dependent distributed filtering design in terms of certain convex optimization problem. The purpose of solving the problem is to design a distributed full- and reduced-order filter such that, in the presence of deception attacks, stochastic external interference and switching topologies, the resulting filtering dynamic system is exponentially mean-square stable with prescribed l 2 - l ∞ performance index. Finally, a simulation example is provided to show the effectiveness and flexibility of the designed approach.

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Trust-based distributed Kalman filtering for target tracking under malicious cyber attacks

Cited by 55 publications

References 57 publications

A Survey on Model-Based Distributed Control and Filtering for Industrial Cyber-Physical Systems

A Survey on Model-Based Distributed Control and Filtering for Industrial Cyber-Physical Systems

Multi-Agent Systems and Complex Networks: Review and Applications in Systems Engineering

Distributed Robust Filtering for Wireless Sensor Networks with Markov Switching Topologies and Deception Attacks

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