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1. On the cybersecurity of smart structures under wind

   https://doi.org/10.1016/j.jweia.2024.105777  

   Cid_Montoya, Miguel; Rubio-Medrano, Carlos E; Kareem, Ahsan (August 2024, Journal of Wind Engineering and Industrial Aerodynamics)

   Controlling wind-induced responses is a challenging and fundamental step in the design of wind-sensitive critical infrastructures (CI). While passive design modifications and passive control devices are effective alternatives to a certain extent, further actions are required to fulfill design specifications under some demanding circumstances. Active countermeasures, such as active dampers, active aerodynamic devices, and operational control systems, stand out as a smart alternative that allows extra control over wind-induced responses of tall buildings, long-span bridges, wind turbines, and solar trackers. To make this possible, CI are equipped with operational technology (OT) and cyber–physical systems (CPS). However, as with any other OT/CPS, these systems can be threatened by cyberattacks. Changing their intended use could result in severe structural damage or even the eventual collapse of the structure. This study analyzes the potential consequences of cyberattacks against wind-sensitive structures equipped with OT/CPS based on case studies reported in the structural control literature. Several cyberattacks, scenarios, and possible defenses, including cyber-secure aero-structural design methods, are discussed. Furthermore, we conceptually introduce and analyze a new cyberattack, the ‘‘Wind-Leveraged False Data Injection’’ (WindFDI), that can be specifically developed by taking advantage of the positive feedback between wind loads and the misuse of active control systems. 

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2. Adversarial Anomaly Detection Using Centroid-Based Clustering

   https://doi.org/10.1109/IRI.2018.00009  

   Anindya, Imrul Chowdhury; Kantarcioglu, Murat (July 2018, 2018 IEEE International Conference on Information Reuse and Integration (IRI))

   As cyber attacks are growing with an unprecedented rate in the recent years, organizations are seeking an efficient and scalable solution towards a holistic protection system. As the adversaries are becoming more skilled and organized, traditional rule based detection systems have been proved to be quite ineffective against the continuously evolving cyber attacks. Consequently, security researchers are focusing on applying machine learning techniques and big data analytics to defend against cyber attacks. Over the recent years, several anomaly detection systems have been claimed to be quite successful against the sophisticated cyber attacks including the previously unseen zero-day attacks. But often, these systems do not consider the adversary's adaptive attacking behavior for bypassing the detection procedure. As a result, deploying these systems in active real-world scenarios fails to provide significant benefits in the presence of intelligent adversaries that are carefully manipulating the attack vectors. In this work, we analyze the adversarial impact on anomaly detection models that are built upon centroid-based clustering from game-theoretic aspect and propose adversarial anomaly detection technique for these models. The experimental results show that our game-theoretic anomaly detection models can withstand attacks more effectively compared to the traditional models. 

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3. Integrated instruction set randomization and control reconfiguration for securing cyber-physical systems

   https://doi.org/10.1145/3190619.3190636  

   Potteiger, Bradley; Zhang, Zhenkai; Koutsoukos, Xenofon (April 2018, HoTSoS '18 Proceedings of the 5th Annual Symposium and Bootcamp on Hot Topics in the Science of Security)

   Cyber-Physical Systems (CPS) have been increasingly subject to cyber-attacks including code injection attacks. Zero day attacks further exasperate the threat landscape by requiring a shift to defense in depth approaches. With the tightly coupled nature of cyber components with the physical domain, these attacks have the potential to cause significant damage if safety-critical applications such as automobiles are compromised. Moving target defense techniques such as instruction set randomization (ISR) have been commonly proposed to address these types of attacks. However, under current implementations an attack can result in system crashing which is unacceptable in CPS. As such, CPS necessitate proper control reconfiguration mechanisms to prevent a loss of availability in system operation. This paper addresses the problem of maintaining system and security properties of a CPS under attack by integrating ISR, detection, and recovery capabilities that ensure safe, reliable, and predictable system operation. Specifically, we consider the problem of detecting code injection attacks and reconfiguring the controller in real-time. The developed framework is demonstrated with an autonomous vehicle case study. 

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4. A state-of-the-art digital factory integrating digital twin for laser additive and subtractive manufacturing processes

   https://doi.org/10.1108/RPJ-03-2023-0113  

   Tariq, Usman; Joy, Ranjit; Wu, Sung-Heng; Mahmood, Muhammad Arif; Malik, Asad Waqar; Liou, Frank (August 2023, Rapid Prototyping Journal)

   This study aims to discuss the state-of-the-art digital factory (DF) development combining digital twins (DTs), sensing devices, laser additive manufacturing (LAM) and subtractive manufacturing (SM) processes. The current shortcomings and outlook of the DF also have been highlighted. A DF is a state-of-the-art manufacturing facility that uses innovative technologies, including automation, artificial intelligence (AI), the Internet of Things, additive manufacturing (AM), SM, hybrid manufacturing (HM), sensors for real-time feedback and control, and a DT, to streamline and improve manufacturing operations. Design/methodology/approachThis study presents a novel perspective on DF development using laser-based AM, SM, sensors and DTs. Recent developments in laser-based AM, SM, sensors and DTs have been compiled. This study has been developed using systematic reviews and meta-analyses (PRISMA) guidelines, discussing literature on the DTs for laser-based AM, particularly laser powder bed fusion and direct energy deposition, in-situ monitoring and control equipment, SM and HM. The principal goal of this study is to highlight the aspects of DF and its development using existing techniques. FindingsA comprehensive literature review finds a substantial lack of complete techniques that incorporate cyber-physical systems, advanced data analytics, AI, standardized interoperability, human–machine cooperation and scalable adaptability. The suggested DF effectively fills this void by integrating cyber-physical system components, including DT, AM, SM and sensors into the manufacturing process. Using sophisticated data analytics and AI algorithms, the DF facilitates real-time data analysis, predictive maintenance, quality control and optimal resource allocation. In addition, the suggested DF ensures interoperability between diverse devices and systems by emphasizing standardized communication protocols and interfaces. The modular and adaptable architecture of the DF enables scalability and adaptation, allowing for rapid reaction to market conditions. Originality/valueBased on the need of DF, this review presents a comprehensive approach to DF development using DTs, sensing devices, LAM and SM processes and provides current progress in this domain. 

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5. Design of a Laboratory Scale Solar Microgrid Cyber-Physical System for Education

   https://doi.org/10.3390/electronics10131562  

   Guo, Liping; Kors, Jason (July 2021, Electronics)

   null (Ed.)

   Renewable energy sources such as solar and wind provide an effective solution for reducing dependency on conventional power generation and increasing the reliability and quality of power systems. Presented in this paper are design and implementation of a laboratory scale solar microgrid cyber-physical system (CPS) with wireless data monitoring as a teaching tool in the engineering technology curriculum. In the system, the solar panel, battery, charge controller, and loads form the physical layer, while the sensors, communication networks, supervisory control and data acquisition systems (SCADA) and control systems form the cyber layer. The physical layer was seamlessly integrated with the cyber layer consisting of control and communication. The objective was to create a robust CPS platform and to use the system to promote interest in and knowledge of renewable energy among university students. Experimental results showed that the maximum power point tracking (MPPT) charge controller provided the loads with power from the solar panel and used additional power to charge the rechargeable battery. Through the system, students learned and mastered key concepts and knowledge of multi-disciplinary areas including data sampling and acquisition, analog to digital conversion, solar power, battery charging, control, embedded systems and software programing. It is a valuable teaching resource for students to study renewable energy in CPS. 

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