Computer Science Presentation: Data-driven CPS/IoT Systems in the AI Era, Dr. Dong Chen, the Department of Computer Science, Colorado School of Mines (Mines)

Abstract:

As Cyber-Physical Systems (CPS) and Internet of Things (IoT) devices become deeply integrated into smart homes, smart grids, and smart cities, they generate vast amounts of network traffic. However, this data can inadvertently expose sensitive user information, making it a target for AI-powered privacy attacks. Unfortunately, existing defense mechanisms often fail to keep up with these evolving threats. In this talk, I will present a data-driven, privacy-friendly CPS/IoT management framework designed to help users identify and mitigate their private information leakage risks. I will begin by introducing the IoT Traffic Exposure Monitoring Toolkit (ITEMTK), an open-source, low-cost system that employs AI-based privacy attack models to uncover vulnerabilities in CPS/IoT environments. First, I will introduce IoT Traffic Exposure Monitoring Toolkit (ITEMTK)—a low-cost, open-source system that includes AI-based privacy attack models to uncover vulnerabilities in CPS/IoT systems. Next, I will discuss my recent advancements in traffic reshaping techniques, including PrivacyGuard, VoiceAttack, and PAROS, which provide novel, low-cost, and distributed solutions to enhance user privacy. Beyond data privacy, I will briefly introduce our work on data-driven cyber-physical energy systems, including SolarFinder and SolarTrader, aimed at making CPS/IoT more sustainable. Finally, I will outline future research directions in designing next-generation computer systems to improve both the security and sustainability of CPS/IoT infrastructures.

Bio:

Dong Chen is a tenure-track Assistant Professor in the Department of Computer Science, Colorado School of Mines (Mines). He received his Ph.D. in Electrical and Computer Engineering from the University of Massachusetts Amherst (UMass Amherst) in 2018, and Ph.D. in Computer Science in 2014 from Northeastern University, China. His research lies at the intersection of Cyber-Physical Systems (CPS), the Internet of Things (IoT), AI@Edge, Embedded AI, Distributed Machine Learning, and Security and User privacy. He directs Cyber-Physical Systems Laboratory (CPSLab) at Mines, where he conducts experimental CPS system research with a focus on improving Cybersecurity, User Privacy and Sustainability of Cyber-Physical Systems (CPS) and the Internet of Things (IoT) systems at different system scales. His research has been published in top-tier CPS/IoT conferences and journals, including IPSN, BuildSys, ICDCS, PerCom, IoTDI, EWSN, CNS, BigData, SECON, MASS, ICCCN, TOSN, TMC, TIOT, TOIT, etc. He is the recipient of the Best Paper Award at ACM BuildSys’20 and was recognized as the Best Paper Runner-Up at ACM EWSN’24. Specially, on his recent CPS/IoT privacy systems research, he received the NSF CAREER Award from the Computer Systems Research (CSR) program in the Division of Computer and Network Systems in 2023. He has also served on the organizing committee (such as General Chair and Publications Chairs) and technical program committee member for multiple ACM/IEEE CPS/IoT leading conferences and the organizing chair for two IEEE CPS workshops. His recent research has been supported by NSF CSR Program, NSA, Cyber Florida Seed Program, NSF RET Program, Google Education, NOAA, and DoE NEXUS Seed Grants.