Interconnected Cyber-physical Systems Research Articles

Fuzzy adaptive resilient decentralized control of nonlinear interconnected cyber-physical systems under false data injection attacks

In this paper, a new fuzzy adaptive resilient decentralized control method is presented for the nonlinear interconnected cyber-physical systems under false data injection (FDI) attacks. Fuzzy logic systems (FLS) are used to model unknown nonlinear dynamics and the FDI attacks are represented by the sum of the system states and unknown time-varying bounded functions. To deal with the problem of the system states are unavailable under FDI attacks, a new coordinate transformation is proposed for control design. By using the backstepping control design theory and Nussbaum function property, a fuzzy adaptive resilient decentralized control scheme is developed, where the Nussbaum functions are employed to deal with the unknown time-varying weight. Then, the stability of the controlled systems is proved by constructing a appropriate Lyapunov function. Finally, the effectiveness of the proposed fuzzy adaptive resilient decentralized control scheme is verified by the simulation and comparison results.

Development and Validation of a Cyber-Physical System Leveraging EFDPN for Enhanced WSN-IoT Network Security.

In the current digital era, Wireless Sensor Networks (WSNs) and the Internet of Things (IoT) are evolving, transforming human experiences by creating an interconnected environment. However, ensuring the security of WSN-IoT networks remains a significant hurdle, as existing security models are plagued with issues like prolonged training durations and complex classification processes. In this study, a robust cyber-physical system based on the Emphatic Farmland Fertility Integrated Deep Perceptron Network (EFDPN) is proposed to enhance the security of WSN-IoT. This initiative introduces the Farmland Fertility Feature Selection (F3S) technique to alleviate the computational complexity of identifying and classifying attacks. Additionally, this research leverages the Deep Perceptron Network (DPN) classification algorithm for accurate intrusion classification, achieving impressive performance metrics. In the classification phase, the Tunicate Swarm Optimization (TSO) model is employed to improve the sigmoid transformation function, thereby enhancing prediction accuracy. This study demonstrates the development of an EFDPN-based system designed to safeguard WSN-IoT networks. It showcases how the DPN classification technique, in conjunction with the TSO model, significantly improves classification performance. In this research, we employed well-known cyber-attack datasets to validate its effectiveness, revealing its superiority over traditional intrusion detection methods, particularly in achieving higher F1-score values. The incorporation of the F3S algorithm plays a pivotal role in this framework by eliminating irrelevant features, leading to enhanced prediction accuracy for the classifier, marking a substantial stride in fortifying WSN-IoT network security. This research presents a promising approach to enhancing the security and resilience of interconnected cyber-physical systems in the evolving landscape of WSN-IoT networks.

A Detection and Response Architecture for Stealthy Attacks on Cyber-Physical Systems

There has been an increased reliance on interconnected Cyber-Physical Systems (CPS) applications. This reliance has caused tremendous growth in high assurance challenges. Due to the functional interdependence between the internal systems of CPS applications, the utilities' ability to reliably provide services could be disrupted if security threats are not addressed. To address this challenge, we propose a multi-level, multi-agent detection and response architecture built on the formalisms of Hidden Markov Models (HMM) and Markov Decision Processes (MDP). We have evaluated the performance of the proposed architecture on one of the critical smart grid applications, Advanced Metering Infrastructure (AMI). This paper utilizes a simulation tool called SecAMI for performance evaluation. A Stealthy attack scenario contains multiple distinct multi-stage attacks deployed concurrently in a network to compromise the system and stop several critical services in a CPS. The results show that the proposed architecture effectively detects and responds to stealthy attack scenarios against Cyber-Physical Systems. In particular, the simulation results show that the proposed system can preserve the availability of more than 93% of the AMI network under stealthy attacks. A future study may evaluate the effectiveness of various stealthy attack strategies and detection and response systems. The high availability of any AMI should be protected against new attack techniques. The proposed system will also determine a distributed IDS's efficient placement for intrusion detection sensors and response nodes within an AMI.

Automated Cybersecurity Tester for IEC61850-Based Digital Substations

Power substations are the crucial nodes of an interconnected grid, serving as the points where power is transferred from the transmission/distribution grids to the loads. However, interconnected cyberphysical systems and communication-based operations at substations lead to many cybersecurity vulnerabilities. Therefore, more sophisticated cybersecurity vulnerability analyses and threat modeling are required during productization phases, and system hardening is mandatory for the commercialization of products. This paper shows the design and methods to test the cybersecurity of multicast messages for digital substations. The proposed vulnerability assessment methods are based on the semantics of IEC61850 Generic Object Oriented Substation Event (GOOSE) and Sampled Value (SV), and cybersecurity features from IEC62351-6. Different case scenarios for cyberattacks are considered to check the vulnerabilities of the device under test (DUT) based on the IEC62351-6 standard. In order to discover security vulnerabilities in a digital substation, the proposed cybersecurity tester will generate malicious packets that compromise the regular functionality. The results show that the proposed cybersecurity testing module is able to detect potential vulnerabilities in multicast messages and the authentication methods (e.g., message authentication code) of multicast communications. Both commercial and simulated devices are used for the case studies.

Sampled-Data Stabilization of Stochastic Interconnected Cyber-Physical Systems Under DoS Attacks

Cyber-physical systems (CPSs) can be accessed and controlled remotely, which increases their application prospects; however, these characteristics also make them more vulnerable to cyberattacks. In addition, an increasing number of resource-saving sampled-data control methods have attracted attention in the field of research. How to ensure the stability of the system that is attacked by cyberattacks and to reduce further the communication resources is a challenge. In this article, we study the security control problem of stochastic interconnected CPSs under two-channel denial-of-service attacks based on sampled-data output-feedback. First, the state observer and controller are designed with only the system output of the sampling points in the nonattack intervals. Next, the time intervals related to stable and unstable dynamics are distinguished. By analyzing the Lyapunov function in the intervals classified as previously mentioned respectively, the relationship between the sampling period and attack characteristics is derived to ensure that the system is globally mean-square uniformly ultimately bounded. The simulation results are presented to substantiate the analysis.

Towards Cyber–Physical Systems Robust to Communication Delays: A Differential Game Approach

Collaboration between interconnected cyber-physical systems is becoming increasingly pervasive. Time-delays in communication channels between such systems are known to induce catastrophic failure modes, like high frequency oscillations in robotic manipulators in bilateral teleoperation or string instability in platoons of autonomous vehicles. This paper considers nonlinear time-delay systems representing coupled robotic agents, and proposes controllers that are robust to time-varying communication delays. We introduce approximations that allow the delays to be considered as implicit control inputs themselves, and formulate the problem as a zero-sum differential game between the stabilizing controllers and the delays acting adversarially. The ensuing optimal control law is finally compared to known results from Lyapunov-Krasovskii based approaches via numerical experiments.

Um estudo bibliométrico das publicações sobre Segurança Cibernética na Indústria 4.0

A 4ª Revolução Industrial (4RI), caracterizada pela combinação de diferentes tecnologias, em diversos graus de maturidade, gera um conjunto de oportunidades de inovação na indústria. Essa revolução, conhecida como Indústria 4.0, teve a origem na Alemanha, dentro de uma estratégia de Estado para tornar o país líder em tecnologia, visando fortalecer a sua competitividade global. O atual ambiente tecnológico da Indústria 4.0 faz uso dos sistemas ciberfísicos interconectados por meio de um conjunto de tecnologias habilitadoras. Com a conectividade desses sistemas, surgem os desafios da Segurança Cibernética, tornando essas questões como uma das principais preocupações dos líderes empresariais. Diante de um cenário para a proteção de dados e informações, esta pesquisa realizou um estudo bibliométrico sobre a produção científica relacionada com a Segurança Cibernética na Indústria 4.0, utilizando uma abordagem quantitativa-qualitativa para mensurar as publicações e as suas características. A análise e discussão dos resultados permitiu identificar as áreas de pesquisa das publicações, os periódicos com maior número de publicações, os autores com trabalhos mais citados, os países e instituições com pesquisas mais relevantes sobre o tema, e a representatividade das palavras-chave utilizadas nas publicações identificadas nas bases de dados Web of Science e Scopus.

A resilient control strategy for cyber-physical systems subject to denial of service attacks: A leader-follower set-theoretic approach

Multi-agent systems are usually equipped with open communication infrastructures to improve interactions efficiency, reliability and sustainability. Although technologically cost-effective, this makes them vulnerable to cyber-attacks with potentially catastrophic consequences. To this end, we present a novel control architecture capable to deal with the distributed constrained regulation problem in the presence of time-delay attacks on the agents&#x02BC communication infrastructure. The basic idea consists of orchestrating the interconnected cyber-physical system as a leader-follower configuration so that adequate control actions are computed to isolate the attacked unit before it compromises the system operations. Simulations on a multi-area power system confirm that the proposed control scheme can reconfigure the leader-follower structure in response to denial of-service &#x0028 DoS &#x0029 attacks.

Methodological foundations of the fourth industrial revolution research

The article conceptualises the stages that humanity has passed on the way of technological development: the transition from agricultural production to the fi rst steam engines, from mastering the power of steam to electricity, from electricity to digital technologies; and, fi nally, the transition that we are witnessing: from digital technologies to the creation of complex interconnected cyber-physical systems based on autonomous self-learning machines.

SafeSec Tropos: Joint security and safety requirements elicitation

The growing convergence of information technology with operational technology and the accordant proliferation of interconnected cyber-physical systems (CPSs) has given rise to several security and safety challenges. One of these refers to systematically identifying coherent, consistent, and non-conflicting security and safety requirements. This paper proposes an integrated method for safety and security requirements engineering for CPSs at the design stage of the system lifecycle. The method identifies security and safety objectives, it systematically elicits a comprehensive list of requirements, and it links these requirements to objectives, thus facilitating the process of resolving conflicts. To provide insight into the operations of the method, we demonstrate its use to the most vulnerable CPSs on board the Cyber-Enabled Ship (C-ES). By utilizing the proposed method, the safety and security objectives of these systems were defined, and their safety and security requirements were identified.

Advancing Cyber-Physical Systems Resilience: The Effects of Evolving Disruptions

Highly interconnected cyber-physical systems (CPSs) and complex networks can enable greater production capabilities and quality of life through their cyber-augmented characteristics. The high level of interconnectedness within CPSs, however, also increases their vulnerabilities to intelligent malware and coordinated attacks. A disrupted part of a CPS can not only cease to function properly, it can also increase the vulnerability of other parts of the CPS due to the interconnections. In this research, we expand on our previous work, the Collaborative Response against Disruption Propagation (CRDP) model and explore the effects of intelligently coordinated attacks on CPSs. This work addresses a severe limitation of the CRDP model: The assumption that disruptions have random targets. In this new work, the adversarial disruption network initially has only limited information about the target CPS network and assumes random targets. Over time, the adversarial disruption network is assumed to utilize decision tree learning algorithm to intelligently learn about the CPS’s response capabilities over time. Then, the disruption network utilizes this learning to improve its attacks by the defense targeting and response protocols. The novel adversarial disruption learning and targeting protocols are simulated and validated with a random network model. The experiments show that the developed protocols defending the disrupted network can significantly stress the CPS’s resilience capabilities. Further research is needed to understand how the role of cyber-collaborative protocols can advance the CPS resilience.

Distributed Secure State Estimation and Control for CPSs Under Sensor Attacks.

In this paper, we investigate the distributed secure state estimation and control problems for interconnected cyber-physical systems (CPSs) with some sensors being attacked. First, by exploring the distinct properties of the unidentifiable attacks to a CPS, an explicit sufficient condition that the secure state estimation problem can be solvable is established. Then distributed preselectors and observers are presented to solve the secure state estimation problems. Furthermore, with the obtained state estimation, fractional dynamic surface-based distributed secure controllers are also proposed for the secure control problem. Theoretical analysis shows that, with the proposed distributed secure observers and controllers, not only the state of the CPS under attacks can be obtained in a given finite time but also the dynamic surface can be achieved and maintained in a finite time. Finally, the results are applied to an islanded micro-grid system as an illustration, which verifies the effectiveness of the proposed schemes.

Temperature Monitoring for Electrical Substations Using Infrared Thermography: Architecture for Industrial Internet of Things

Large corporations require smart interconnected cyber-physical systems that can interact and cooperate to reach common goals. The design of complex monitoring and fault detection systems based on this approach, usually referred to as Industrial Internet of Things, creates interconnected physical systems that generate value by providing more efficient manufacturing opportunities. However, this approach also creates important challenges, as the large number of sensors and devices provokes difficulties for configuration, application deployment, and service generation. This paper presents solutions for this advanced automation model, proposing an architecture for temperature monitoring and fault detection in electrical substations using infrared thermography. In this paper, systematic methods to apply flexible configurations and deployments are presented, including robust procedures to measure and monitor the temperature of electrical components. Architectural abstractions are also identified for this particular scenario. The proposed methodology and architecture are validated in a real-life case study in a large industrial organization.

Step-based evolution support among networked production automation systems

Abstract Production systems are no longer rigid, unyielding, and isolated systems anymore. They are rather interconnected cyber-physical systems with an evolution process that needs to be supported. To enable reusability in evolution, a change-first cooperative support is proposed that relies on model-based evolution steps. The approach establishes a network-wide evolution process in a peer-to-peer networked community. Thus, moving towards decentralised marketplaces for evolution steps.

IoT-Enabled Highway Maintenance: Understanding Emerging Cybersecurity Threats

IoT technologies are increasingly being deployed to support the operation and maintenance of complex highway infrastructure assets. However, the use of interconnected cyber-physical systems in such critical infrastructure raises important privacy, security, and safety issues. While these issues are well studied in IoT transportation systems and autonomous vehicles, little research relates to highway maintenance systems. In this article, we introduce the problem domain, evince the lack of prior research, and discuss example threats based on a real-world case study.

Distributed Sensor Fault Diagnosis for a Network of Interconnected Cyberphysical Systems

This paper proposes a distributed methodology for detecting and isolating multiple sensor faults in interconnected cyberphysical systems. The distributed sensor fault detection and isolation process is conducted in the cybersuperstratum, in two levels. The first-level diagnosis is based on the design of monitoring agents, where every agent is dedicated to a corresponding interconnected subsystem. The monitoring agent is designed to isolate multiple sensor faults occurring in the sensor set of the physical part, while it is allowed to exchange information with its neighboring monitoring agents. The second-level diagnosis is realized by applying a global decision logic designed to isolate multiple sensor faults that may propagate in the cybersuperstratum through the exchange of information between monitoring agents. The decision-making process, executed in both levels of diagnosis, relies on a multiple sensor fault combinatorial logic and diagnostic reasoning. The performance of the proposed methodology is analyzed with respect to the sensor fault propagation effects and the distributed sensor fault detectability.