K-Corruption Intermittent Attacks for Violating the Codiagnosability

Ruotian Liu; Yihui Hu; Agostino Marcello Mangini; Maria Pia Fanti

doi:10.1109/JAS.2024.124680

IEEE/CAA Journal of Automatica Sinica

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R. Liu, Y. Hu, A. Mangini, and M. Fanti, “K-corruption intermittent attacks for violating the codiagnosability,” IEEE/CAA J. Autom. Sinica, vol. 12, no. 1, pp. 1–14, Jan. 2025. doi: 10.1109/JAS.2024.124680

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R. Liu, Y. Hu, A. Mangini, and M. Fanti, “K-corruption intermittent attacks for violating the codiagnosability,” IEEE/CAA J. Autom. Sinica, vol. 12, no. 1, pp. 1–14, Jan. 2025. doi: 10.1109/JAS.2024.124680

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K-Corruption Intermittent Attacks for Violating the Codiagnosability

doi: 10.1109/JAS.2024.124680

Funds: This work was supported in part by the IN2CCAM project that has received funding from the European Union’s Horizon Europe research and innovation programme (101076791), the National Natural Science Foundation of China (62403378), and the Natural Science Basic Research Program of Shaanxi Province (2024JC-YBQN-0669). This manuscript reflects only the authors’ views and opinions, neither the European Union nor the European Commission can be considered responsible for them

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Author Bio:
Ruotian Liu (Member, IEEE) received the B.S. degree in automation from Xidian University, in 2015, and M.S. and the Ph.D. degrees in automation from Aix-Marseille University, France, in 2018 and 2021, respectively. In 2022, he joined Polytechnic University of Bari, Italy, where he is currently an Assistant Professor with the Department of Electrical and Information Engineering. His research interests include diagnosability/opacity analysis, and supervisory control of discrete event systems and hybrid systems

Yihui Hu received the B.S. degree in electrical engineering and automation from Xi’an University of Architecture and Technology, in 2016, the first Ph.D. degree in control theory and control engineering from Xidian University, in 2021, and the second Ph.D. degree in electronic and computer engineering from the University of Cagliari, Italy, in 2021. He is currently an Associate Professor with the School of Automation, Xi’an University of Posts and Telecommunications. His current research interests include discrete event systems, automata, Petri nets, fault diagnosis, and supervisory control theory

Agostino Marcello Mangini (Senior Member, IEEE) received the laurea degree in electronics engineering and the Ph.D. degree in electrical engineering from the Polytechnic University of Bari, Italy, in 2003 and 2008, respectively. He has been a Visiting Scholar with the University of Zaragoza, Spain. He is currently an Associate Professor with the Department of Electrical and Information Engineering, Polytechnic University of Bari. He has authored or coauthored over 140 printed publications. His current research interests include modeling, simulation, control of discrete-event systems, Petri nets, deep reinforcement learning, supply chains and urban traffic networks, distribution, and internal logistics. He was on the program committees of the 2007–2023 IEEE International SMC Conference on Systems, Man, and Cybernetics. He was on the Editorial Board of the 2017–2023 IEEE Conference on Automation Science and Engineering. Moreover, he was the Publication Chair of the 2017 IEEE SOLI and the 2019 IEEE SMC conferences, the Workshop Co-Chair of the 2023 IEEE SMC conference, the Workshop and Tutorial Chair of the 2023 IEEE CASE Conference, and the Special Session Chair of the 3rd IEEE International Conference on Automation in Manufacturing, Transportation and Logistics (iCaMaL2023). He is an Associate Editor of IEEE Transactions on Automation and Science and Engineering and IEEE Systems, Man, and Cybernetics Magazine

Maria Pia Fanti (Fellow, IEEE) received the laurea degree in electronic engineering from the University of Pisa, Italy, in 1983. She was a Visiting Researcher at the Rensselaer Polytechnic Institute of Troy, USA, in 1999. Since 1983, she has been with the Department of Electrical and Information Engineering of the Polytechnic of Bari, Italy, where she is currently a Full Professor of system and control engineering and Chair of the Laboratory of Automation and Control. Her research interests include management and modeling of complex systems, such as intelligent transportation, logistics and manufacturing systems, discrete event systems, Petri nets, consensus protocols, fault detection. Prof. Fanti has published more than 350 papers and two textbooks on her research topics.She is Senior Editor of the IEEE Transactions on Automation Science and Engineering, and Associate Editor of the IEEE Transactions on Systems, Man, and Cybernetics: Systems and the IEEE Transactions on Intelligent Vehicles. She was Member of the Board of Governors of the IEEE Systems, Man, and Cybernetics Society, and of the Administrative Committee of the IEEE Robotics and Automaton Society, Founder and Chair of the Technical Committee on Automation in Logistics of the IEEE Robotics and Automation Society. Prof. Fanti was General Chair, Program Chair and Member of the organizing committee of a large number of international conference in particular she was General Chair of the 2011 IEEE Conference on Automation Science and Engineering, the 2017 IEEE International Conference on Service Operations and Logistics, and Informatics and the 2019 IEEE Systems, Man, and Cybernetics Conference
Corresponding author: Ruotian Liu, e-mail: ruotian.liu@poliba.it
Received Date: 2024-05-04
Accepted Date: 2024-07-17

Available Online: 2024-09-29

Abstract

Abstract

In this work, we address the codiagnosability analysis problem of a networked discrete event system under malicious attacks. The considered system is modeled by a labeled Petri net and is monitored by a series of sites, in which each site possesses its own set of sensors, without requiring communication among sites or to any coordinators. A net is said to be codiagnosable with respect to a fault if at least one site could deduce the occurrence of this fault within finite steps. In this context, we focus on a type of malicious attack that is called stealthy intermittent replacement attack. The stealthiness demands that the corrupted observations should be consistent with the system’s normal behavior, while the intermittent replacement setting entails that the replaced transition labels must be recovered within a bounded of consecutive corrupted observations (called as K-corruption intermittent attack). Particularly, there exists a coordination between attackers that are separately effected on different sites, which holds the same corrupted observation for each common transition under attacks. From an attacker viewpoint, this work aims to design K-corruption intermittent attacks for violating the codiagnosability of systems. For this purpose, we propose an attack automaton to analyze K-corruption intermittent attack for each site, and build a new structure called complete attack graph that is used to analyze all the potential attacked paths. Finally, an algorithm is inferred to obtain the K-corruption intermittent attacks, and examples are given to show the proposed attack strategy.
- Codiagnosability,
- decentralized structure,
- discrete event system,
- intermittent attack,
- Petri net

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References

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K-Corruption Intermittent Attacks for Violating the Codiagnosability

doi: 10.1109/JAS.2024.124680

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