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Keynote Speakers

Artificial Intelligence in Cyber-Physical Systems, Friend or a Foe

Milos Manic

Virginia Commonwealth University, Richmond, USA

The most recent advancements in Artificial Intelligence (AI) have provided unprecedented opportunities for real-time understanding of overall behavior and health of complex systems. The talk will focus on presenting the latest advancements in AI based on real-world case studies. We will investigate the capabilities of cutting-edge AI techniques for sequence modeling, demonstrating its ability to understand complex patterns and understand complex systems with high accuracy.
Furthermore, we will look at the approaches to modern tools for explaining AI decisions. In an environment where quick decision-making is critical, the collaboration of AI and human expertise becomes essential. We will emphasize the importance of explainability and interactive visualizations in encouraging effective cooperation between humans and AI, particularly when faced with massive volumes of data and little time for informed decision-making. In addition, we will investigate incorporating human knowledge and physics into the AI system to fill the gap of missing data, as well as facilitating effective knowledge transfer between anomaly detection models designed for different systems.
The talk will conclude with the brief overview of IEEE Industrial Electronics Society activities and opportunities for volunteer engagements.

''Dr. Manic is a Professor with the Computer Science Department and Director of VCU Cybersecurity Center at Virginia Commonwealth University. He completed over 50 research grants in AI/ML in cyber and energy and intelligent controls. He authored over 200 refereed articles, has given over 50 invited talks around the world, authored over 200 refereed articles in international journals, books, and conferences, holds several U.S. patents and has won 2018 R&D 100 Award for Autonomic Intelligent Cyber Sensor (AICS), one of top 100 science and technology worldwide innovations in 2018, and is recipient of the 2023 FBI DCLA Director’s Community Leadership Award for innovative research in AI & cybersecurity.
He is an inductee of US National Academy of Inventors (senior class of 2023, member class of 2019), and a Fellow of Commonwealth Cyber Initiative (specialty in AI & Cybersecurity). He holds Joint Appointment with Idaho National laboratory.
He is an IEEE IES President (2024-2025), after serving in multiple IES officer positions, IEEE Fellow (for contributions to machine learning based cybersecurity in critical infrastructures), recipient of IEEE IES 2019 Anthony J. Hornfeck Service Award, 2012 J. David Irwin Early Career Award, 2017 IEM Best Paper Award, associate editor of IEEE Transactions on Industrial Informatics, IEEE Open Journal of Industrial Electronics Society, and IEEE IES Senior Life AdCom member. He served as AE of Trans. on Industrial Electronics, was a founding chair of IEEE IES Technical Committee on Resilience and Security in Industry, and was a General Chair of IEEE ICIT 2023, IEEE IECON 2018 (record breaking, over 1,100 participants), IEEE HSI 2019.''



Proving probabilistic worst-case reasoning: when functional and non-functional properties must meet

Liliana Cucu-Grosjean

French National Institute in Computer Science and Automation (Inria) in Paris, France

The problem of identifying and proving worst-case time behavior of real-time programs on processors has appeared within the context of critical industries like avionics or space. Rapidly adopted by the real-time scheduling community, worst-case execution time estimates of programs or tasks are mandatory to understand the time behaviour of a real-time system. Analyzing such time behaviour is often, done, with an important pessimism due to the consideration of worst-case scenarios, especially for multicore processors. A decreased pessimism has been obtained by understanding that large execution times of a program have low probability of appearance. Probabilistic (worst-case) execution time notion has been proposed, while current approaches are built, often, on statistical estimators based on the use of Extreme Value Theory or concentration inequalities. Recent results revisiting these definitions underline the maturity of their applicability but also the need of a correct and proved reasoning. Within this talk, we discuss a possible dilemma: a proved probabilistic (or statistical) worst-case reasoning may impose a joint analysis of both functional and non-functional properties. Nevertheless, these properties are analyzed separately when certified executions of programs are required in critical industries like avionics or space and this separation seems to be a mandatory key towards a successful certification process.

''Liliana Cucu-Grosjean is a Research Director at the French National Institute in Computer Science and Automation (Inria) in Paris, France, where she leads the Kopernic research team. Her research interests include real-time, embedded and cyber-physical systems with a focus on the use of probabilistic and statistical methods for analyzing the schedulability of programs and estimating worst-case execution of those programs. Co-author of several seminal papers on probabilistic and statistical methods for real-time systems, Liliana has published more than 60 papers in top TCRTS conferences and journals. She has served the community by acting as (General, TPC/track/topic and local) chair for important venues of the TCRTS community (RTSS, RTCSA and RTNS) as well as strongly-related venues (DATE for architecture-oriented topics and MAPSP and ROADEF for scheduling-oriented events). Co-founder of workshops like WMC (RTSS joint workshop), JWRTC (RTNS joint workshop) and Dagstuhl series on mixed criticality, she has helped consolidating the diversity actions among under-represented categories of researchers. Chair of the first TCRTS diversity sub-committees 1 (2016 to 2020), she has also co-founded the Inria diversity committee in 2015, that she co-chaired until 2022. Since January 2023, she has been the elected IEEE TCRTS vice-chair. Her contributions to a correct utilization of statistical approaches for the worst-case execution time estimation problem have been transferred from Inria to the start-up StatInf, an Inria spin-off that she co-founded in 2019. This patented technology has received numerous industry awards like the French most innovative technology in 2022 at the prestigious Assises de l’Embarqué and cited among the top 100 innovations expected to change the everyday life by the Le Point newspaper (July 2023) and among top 100 most influential Romanian in 2023. Last, but not least, the start-up StatInf is named among the 15 top France Analytics Startups in 2023 by EU Startup news online media (August 2023).

1* The first TCRTS diversity sub-committee has been created by Prof. James H. Anderson and continued since by the TCRTS chairs''


Adversary Emulation in the Age of Generative AI

Roberto Natella

Università degli Studi di Napoli Federico II, Italy

Cybersecurity threat actors have been evolving into complex organizations, with technical and financial means to deliver powerful attacks, with significant impact on economy and infrastructures. These threat actors are also looking with high interest at the recent evolution of Generative AI for malicious purposes. Generative AI is also a valuable opportunity to enhance cybersecurity. This presentation will look at emerging applications of Generative AI for Adversary Emulation, that is, the emulation of attack techniques for assessment purposes. In particular, we will discuss the role of Large Language Models (LLMs) at supporting cybersecurity analysts, by automatically generating malicious code to mimic threat actors.

''Roberto Natella is an Associate Professor in Computer Engineering at the Federico II University of Naples, Italy. In 2022, Roberto received the DSN Rising Star in Dependability Award from the IEEE Technical Committee on Dependable Computing and Fault Tolerance (TCFT) and the IFIP Working Group 10.4 on Dependable Computing and Fault Tolerance, for research achievements within 10 years after PhD graduation.

His research interests are in the field of software security and dependability. The main recurring theme of his research activity is the experimental injection of faults, attacks, and stressful conditions.''


Leveraging LLMs for Secure and Trustworthy Software: Insights and Future Perspectives

Marco Vieira

University of North Carolina at Charlotte, USA

Large Language Models (LLMs) are transforming software engineering, offering new possibilities for developing secure and trustworthy software. This keynote will explore the integration of LLMs into software development workflows, particularly their role in code generation. Supported by empirical evidence, we will discuss the capabilities of LLMs in vulnerability detection and mitigation, and delve into the importance of assessing the trustworthiness of code, including the role of LLMs in verifying code quality and adherence to best practices. We will conclude with a discussion on future directions, outlining emerging opportunities for LLMs in software engineering.

''Marco Vieira was born in Ponte de Lima, Portugal. He earned his Ph.D. in Informatics Engineering from the University of Coimbra, Portugal. Marco Vieira is a Professor in the College of Computing and Informatics at the University of North Carolina at Charlotte. Before joining UNC Charlotte in 2023, he was a Professor at the University of Coimbra. His research interests include dependable computing, dependability and security assessment and benchmarking, software security, fault and vulnerability injection, failure prediction, static analysis and software testing, subjects in which he authored or co-authored works in refereed conferences and journals.

Marco is Chair of the IFIP WF 10.4 on Dependable Computing and Fault Tolerance, Associate Editor of the IEEE Transactions on Dependable and Secure Computing, Steering Committee Vice-Chair of the IEEE/IFIP International Conference on Dependable Systems and Networks, and member of the Steering Committee of the IEEE International Symposium on Software Reliability Engineering. He served as Program Chair for the major conferences on the dependable computing area.''