Cyber-Physical Systems

Also known as CPS

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12 papers in the last four weeks, against 2 the four weeks before. 0.1% of all new papers.

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Latest papers 57

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Explaining Failures of Cyber-Physical Systems with Actual Causality
Jun 23, 2026Khen Elimelech, Tom Yaacov, David A. Kelly +2Agent Failure Analysis Cyber-Physical Systems
King’s College London · Rice University
Pseudo-Feature Padding: A Lightweight Defense Against False Data Injection in Power Grids
Jun 18, 2026Farhin Farhad Riya, Shahinul Hoque, Yingyuan Yang +2Cyber-Physical Systems False Data Injection Attacks
Department of Electrical Engineering and Computer Science, University of Tennessee · Department of Computer Science, The University of Illinois at Springfield · Department of Electrical and Computer Engineering, Clemson University, South Carolina
Model-Free Reinforcement Learning Control for Resilient Cyber-Physical Systems
Jun 17, 2026Hugo O. Garcés, Alejandro J. Rojas, Bernardo A. Hernández +5RL Control Cyber-Physical Systems
Departamento de Ingeniería Informática y Ciencias de la Computación, Universidad de Concepción, Concepción, Chile · Electrical Engineering Departament, Universidad de Talca · Department of Electrical & Computer Engineering, University of Alberta, Edmonton, T6G 1H9, Alberta, AB, Canada +2
AI Sandboxes: A Threat Model, Taxonomy, and Measurement Framework
Jun 16, 2026Inderjeet Singh, Haitham Mahmoud, Andrés MurilloCyber-Physical Systems AI Assurance
Fujitsu Research of Europe, United Kingdom
TRIDENT: Breaking the Hybrid-Safety-Physics Coupling for Provably Safe Multi-Agent Reinforcement Learning
Jun 16, 2026Zijie Meng, Ziwei Li, Yufei Liu +5Cyber-Physical Systems Reinforcement Learning
Peking University · National Taiwan University · WHU +1
Graph neural networks at war: integrating cybersecurity and drone intelligence in the Israeli-Iranian conflict
Jun 15, 2026Sozan Sulaiman Maghdid, Tarik Ahmed Rashid, Shavan AskarCyber-Physical Systems Autonomous Cyber Defense
Department of Information Technology, Khabat Technical Institute; Erbil Polytechnic University, Erbil, Iraq · Computer Science and Engineering Department; AIIC, University of Kurdistan Hewler, Erbil, Iraq · Department of Information Systems Engineering, Technical College of Computer and Informatics Engineering, Erbil Polytechnic University, Erbil, Iraq
A Formal Resilience Framework for Cyber-Physical Embodied Systems under Device-Level Cyberattacks
Jun 15, 2026Alberto GiarettaCyber-Physical Systems Cybersecurity
Department of Computer Science, Örebro University, Sweden · AI, Robotics and Cybersecurity Center (ARC), Örebro University, Sweden
Tessellated Biomes: Distributed Robotic Assemblies for Architectural Resilience
Jun 7, 2026Sergio Mutis, Eric Hughes, Gert DuvenhageCyber-Physical Systems Robotic Construction
MIT · UCL
AI-Native Closed-Loop Security for 6G-Enabled Cyber-Physical Systems: From Edge Detection to Network-Wide Mitigation
Jun 6, 2026Bilal Hussain, Muhammad Bilal, Tan Li +6Cyber-Physical Systems 6G Networks
Division of Science, Engineering, and Health Studies, School of Professional Education and Executive Development, The Hong Kong Polytechnic University, Hong Kong SAR, China · School of Computing and Communications, Lancaster University, United Kingdom · Department of Computer Science, The Hang Seng University of Hong Kong, Hong Kong SAR, China +4
IDDMBSE: Integrating Data-Driven and Model-Based Systems Engineering for Trusted Autonomous Cyber-Physical Systems
Jun 4, 2026John S. Baras, Sai Sandeep Damera, Ryan Matheu +2Cyber-Physical Systems Model-Based Systems Engineering
Institute for Systems Research, University of Maryland, College Park, MD, USA
Attack Detection using Time Series Foundation Models
Jun 4, 2026Sribalaji C. Anand, Anh Tung Nguyen, George J. PappasCyber-Physical Systems Cybersecurity
University of Pennsylvania, United States · Uppsala University, Sweden
IstGPT: LLM-based Anomaly Detection for Spatial-Temporal Graph in Industrial Systems
Jun 1, 2026Yuchen Zhang, Ning Xi, Pengbin Feng +5Cyber-Physical Systems Industrial Anomaly Detection
School of Cyber Engineering, Xidian University, Xi’an 710126, China · School of Science, Computing and Engineering Technologies, Swinburne University of Technology, Hawthorn, VIC, Australia · School of Computer Science and Technology, Xidian University, Xi’an 710126, China
Backdoor Attacks on Fault Detection and Localization in Cyber-Physical Systems
May 26, 2026Abile Jean, Kuniyilh SCyber-Physical Systems Backdoor Attacks
When Agents Control Robots: A Zero Trust Policy Model for Agentic Cyber-Physical Systems
May 25, 2026Tharindu Ranathunga, Kavishka Fernando, Susan ReaRobotic Control Cyber-Physical Systems
Nimbus Centre, Munster Technological University, Cork, Ireland
ASTRO: Adaptive Spatio-Temporal Reinforcement Optimization for GNN Powered Anomly Detection in Cyber Physical Systems
May 24, 2026Rai Ali Yar, Umaisa Lail, Anwar ShahCyber-Physical Systems Online Anomaly Detection
Department of Computer Science, FAST NUCES, Development Sector, Faisalabad, Pakistan · Department of Information Technology, Riphah International University, Faisalabad, Pakistan
Cyber-Physical Anomaly Detection in IoT-Enabled Smart Grids Using Machine Learning and Metaheuristic Feature Optimization
May 21, 2026Adis Alihodžić, Eva Tuba, Milan TubaCyber-Physical Systems Cybersecurity
Department of Mathematical and Computer Sciences, University of Sarajevo, Zmaja od Bosne 33–35, Sarajevo, 71000, Bosnia & Herzegovina · Singidunum University, Danijelova 32, Belgrade, 11000, Serbia · Trinity University, 1 Trinity Pl, San Antonio, 78212, Texas, USA +1
KAPPS: A knowledge-based CPPS Architecture for the Circular Factory
May 21, 2026Etienne Hoffmann, Jan-Felix Klein, Sören Weindel +7Manufacturing Cyber-Physical Systems
Institute for Material Handling and Logistics (IFL), Karlsruhe Institute of Technology, Karlsruhe, Germany · Department of Production Engineering, KTH Royal Institute of Technology, Stockholm, Sweden · Institute of Production Science (wbk), Karlsruhe Institute of Technology, Karlsruhe, Germany +2
GenAI-FDIA: Physics-Informed Generative Models for False Data Injection Attacks
May 15, 2026Mohammad A. Razzaque, Muta Tah HiraCyber-Physical Systems Physics-Informed Generative Modeling
School of Computing, Engineering and Digital Technologies, Teesside University, UK · Smartifier Ltd, Stockton-on-Tees, UK
Quantifying Cyber-Vulnerability in Power Electronics Systems via an Impedance-Based Attack Reachable Domain
May 14, 2026Hongwei Zhen, Ze Yu, Xin Xiang +2Cyber-Physical Systems Reachability Analysis
Product-Aware Deep Autoencoders for Robust Process Monitoring in Multi-Product Cyber-Physical Systems
May 13, 2026MD Shafikul Islam, Jordan CardenCyber-Physical Systems Autoencoders
Benchmarking Sensor-Fault Robustness in Forecasting
May 11, 2026Alexander Windmann, Philipp Wittenberg, Gianluca Manca +3Cyber-Physical Systems Time Series Forecasting
1Helmut Schmidt University · 2Ruhr University Bochum · 3ABB Corporate Research +2
PhaseNet++: Phase-Aware Frequency-Domain Anomaly Detection for Industrial Control Systems via Phase Coherence Graphs
Apr 30, 2026Raviteja Bommireddy, Varshith Bandaru, Lohith Pakala +1Cyber-Physical Systems Frequency-Domain Feature Learning
Department of CSE IIITDM Kancheepuram Chennai, India
SMSI: System Model Security Inference: Automated Threat Modeling for Cyber-Physical Systems
Apr 26, 2026RoÝah Radaideh, Ali KhreisCyber-Physical Systems Cybersecurity
School of Electrical Engineering and Computer Science, University of Ottawa, Ottawa, ON, Canada
Grammar-Constrained Refinement of Safety Operational Rules Using Language in the Loop: What Could Go Wrong
Apr 26, 2026Khouloud Gaaloul, Zaid Ghazal, Madhu Latha Pulimi +1Cyber-Physical Systems Safety-Critical Control
University of Michigan–Dearborn Dearborn, MI, USA
Architectures for Robust Self-Organizing Energy Systems under Information and Control Constraints
Apr 23, 2026Emilie Frost, Astrid NießeCyber-Physical Systems Robust Control
Department of Computing Science, Carl von Ossietzky Universität Oldenburg, Ammerländer Heerstraße 114-118, Oldenburg, Germany · Distributed Artificial Intelligence, OFFIS - Institute for Information Technology, Escherweg 2, Oldenburg, Germany
Retrieval Augmented (Knowledge Graph), and Large Language Model-Driven Design Structure Matrix (DSM) Generation of Cyber-Physical Systems
Jan 30, 2026H. Sinan Bank, Daniel R. HerberCyber-Physical Systems Retrieval-Augmented Generation
Department of Systems Engineering, Colorado State University, Fort Collins, CO 80523, USA
PEARL: Structural Privacy-Utility Control in Human-Centric CPS via Personalized Early-Exit Deep Reinforcement Learning
Date pendingMojtaba Taherisadr, Salma ElmalakiRL Control Cyber-Physical Systems
University of California, Irvine, USA

Jun 23, 2026, cs.ROJ/K move · Enter open · S save

Explaining Failures of Cyber-Physical Systems with Actual Causality

Khen Elimelech, Tom Yaacov, David A. Kelly, Hana Chockler+1

King’s College London · Rice University

Agent Failure Analysis Cyber-Physical Systems Actual Causality Causal Reasoning Causal Explanation

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Modern autonomous Cyber-Physical Systems (CPSs), such as self-driving cars, face increasingly complex demands, and yet are expected to act reliably. The black-box nature often characterizing such systems, especially those relying on neural components, makes it impossible to fully verify the system behavior prior to deployment. Unfortunately, unexpected failures-when the system does not comply with its specification-are inevitable and may have catastrophic implications. To improve trust in the system and facilitate future mitigation after a failure occurs, it is important to try to derive an explanation for the unexpected system behavior. This paper introduces the novel concept of leveraging the framework of actual causality for CPS failure explanation. Up until now, this framework was only used to derive explanations in the context of simple systems, such as image classifiers. This paper addresses the theoretical gaps and provides the guidance needed to allow for correct explanation derivation in the CPS domain. Beyond the theoretical contribution, the paper presents two novel, practical, system-agnostic explanation derivation algorithms, allowing to prioritize either explanation optimality or derivation efficiency. The approach is demonstrated and evaluated in the context of a neural-network-controlled autonomous car, designed to avoid collisions.

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Latest papers 57