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Our Critical Infrastructure (CI) systems are, by definition, critical to the safe and proper functioning of society. Nearly all of these systems utilize industrial Process Control Systems (PCS) to provide clean water, reliable electricity,…
As large language models (LLMs) become increasingly integrated into daily applications, it is essential to ensure they operate fairly across diverse user demographics. In this work, we show that LLMs suffer from personalization bias, where…
Pipeline bursting, production lines shut down, frenzy traffic, trains confrontation, nuclear reactor shut down, disrupted electric supply, interrupted oxygen supply in ICU - these catastrophic events could result because of an erroneous…
Industrial control system (ICS) operations use trusted endpoints like human machine interfaces (HMIs) and workstations to relay commands to programmable logic controllers (PLCs). Because most PLCs lack layered defenses, compromise of a…
Model Predictive Control (MPC) is a powerful and flexible design tool of high-performance controllers for physical systems in the presence of input and output constraints. A challenge for the practitioner applying MPC is the need of tuning…
Usability engineering is situated in a much larger social and institutional context than is usually acknowledged by usability professionals in the way that they define their field. The definitions and processes used in the improvement of…
Interpretability, trustworthiness, and usability are key considerations in high-stake security applications, especially when utilizing deep learning models. While these models are known for their high accuracy, they behave as black boxes in…
OpenClaw-like agents offer substantial productivity benefits, yet they are insecure by default because they combine untrusted inputs, autonomous action, extensibility, and privileged system access within a single execution loop. We use…
Distributed implementations of access control abound in distributed storage protocols. While such implementations are often accompanied by informal justifications of their correctness, our formal analysis reveals that their correctness can…
Current day software development relies heavily on the use of service architectures and on agile iterative development methods to design, implement, and deploy systems. These practices result in systems made up of multiple services that…
Due to significant improvements in performance in recent years, neural networks are currently used for an ever-increasing number of applications. However, neural networks have the drawback that their decisions are not readily interpretable…
DevOps has become a dominant paradigm in modern software engineering, while low-code development platforms (LCDPs) are increasingly adopted to streamline software development. The integration of these approaches promises efficiency gains…
Power side-channel (PSC) attacks are widely used in embedded microcontrollers, particularly in cryptographic applications, to extract sensitive information. However, expanding the applications of PSC attacks to broader security contexts in…
The management of data and digital assets poses various challenges, including the need to adhere to legal requirements with respect to personal data protection and copyright. Usage control technologies could be used by software platform…
With the growth of embedded systems, VLSI design phases complexity and cost factors across the globe and has become outsourced. Modern computing ICs are now using system-on-chip for better on-chip processing and communication. In the era of…
Autonomous cyber-physical systems (CPS) rely on the correct operation of numerous components, with state-of-the-art methods relying on machine learning (ML) and artificial intelligence (AI) components in various stages of sensing and…
Software needs to be secure, in particular, when deployed to critical infrastructures. Secure coding guidelines capture practices in industrial software engineering to ensure the security of code. This study aims to assess the level of…
The growing use of Machine Learning and Artificial Intelligence (AI), particularly Large Language Models (LLMs) like OpenAI's GPT series, leads to disruptive changes across organizations. At the same time, there is a growing concern about…
We witness an increasing usage of AI-assistants even for routine (classroom) programming tasks. However, the code generated on basis of a so called "prompt" by the programmer does not always meet accepted security standards. On the one…
As large language models (LLMs) are increasingly integrated into numerous applications across various domains, LLMs' safety becomes a critical concern for both application developers and intended users. Currently, great efforts have been…