IstGPT introduces a novel LLM-based framework for real-time, fine-grained anomaly detection in complex industrial cyber-physical systems, achieving state-of-the-art performance across multiple benchma…

This paper analyzes the potential downsides of integrating advanced AI and smart capabilities across the Edge-Cloud continuum in modern industry, focusing specifically on security vulnerabilities, sid…

This paper proposes a methodology for detecting control valve stiction in industrial processes using optimal transport imaging and deep correlation alignment.

The paper reframes industrial visual sim-to-real transfer as a domain-gap problem categorized by the availability of explicit object geometry (CAD), arguing that the required prior evidence dictates t…

The paper proposes a clustering-enhanced domain adaptation method that significantly improves cross-domain intrusion detection in industrial control systems by aligning feature distributions and enhan…

This paper proposes a scheme to coordinate 5G and TSN schedulers for supporting deterministic communications with bounded latencies in industrial applications.

AFL-ICP is a novel specification-driven fuzzing framework that significantly enhances the security testing of industrial control protocols by detecting subtle semantic and logic bugs missed by traditi…

SCARA is a novel, end-to-end framework that autonomously connects binary-level vulnerability candidates to conditionally validated remedies for opaque industrial software, achieving high precision and…

The study compared LLM-based conversational agents (CAs) and traditional dashboards for industrial decision support, finding that while CAs reduce mental workload in simple tasks, neither interface pr…

The paper introduces APIOT, the first LLM framework capable of autonomously performing the full discovery, exploitation, patching, and verification cycle against bare-metal industrial OT devices.

This paper proposes a lightweight, multi-layer Machine Learning-based security framework for Industrial IoT (IIoT) to enhance trust convergence and detect advanced threats.

This paper details the process of architecting and releasing LINICS, an open-source platform designed to provide necessary pentesting and security analysis capabilities for Operational Technology (OT)…

The paper proposes a policy-neutral execution and measurement layer to mediate between reinforcement learning policies and industrial environments, transforming ambiguous execution failures into struc…

The paper proposes an end-to-end, deployable blueprint for an in-line machine-vision system that not only inspects carpet defects in real-time but also systematically collects and labels defect data t…

The paper reframes manufacturing ransomware recovery from a simple backup restoration task to a complex critical-infrastructure continuity problem, proposing Minimum Viable Factory Recovery (MVF Recov…

This paper proposes an automated method to generate complete PDDL planning problems directly from Asset Administration Shell (AAS) capability models, eliminating the need for specialized planning expe…

The paper proposes a semi-automated framework that integrates network topology and vulnerability data to generate and analyze multi-step attack graphs in Industrial Control Systems, demonstrated using…

This paper discusses the significant challenges in developing a holistic intrusion detection system for Industrial Control Systems (ICS) that must cover all operational dimensions.

The paper proposes a graph attention-based virtual metrology framework that accurately predicts film thickness in semiconductor deposition by modeling structured, directional dependencies among hetero…

This paper presents hardware-faithful verification for IEC 61131-3 on low-cost microcontrollers, reducing false alarms and preserving robustness proofs.