- Remote Access - Zoom
- Virtual Presentation - ET
Each presentation will be about 30 minutes including Q&A.
► Terrance Liu- presenting on behalf of Professors Yuvraj Agarwal and Steven Wu — Enabling Privacy-Preserving IoT Apps and Data Analytics
→ In this talk, we will first provide a quick overview of our comprehensive framework for differentially private synthetic data release. We will then briefly discuss our ongoing work that applies our framework to IoT data.
- Terrance Liu is currently a research assistant working under Steven Wu. His research is centered around machine learning and privacy, with a focus on differentially private synthetic data generation. His recent work was accepted as a poster at ICML'21 and received best paper awards at the DPML and SGD workshops held at ICLR'21. He completed his M.S. in machine learning at Carnegie Mellon University and B.S. in mathematics and economics at the University of Chicago.
- Yuvraj Agarwal is an Assistant Professor in the School of Computer Science, within the Institute for Software Research, at Carnegie Mellon University. His research interests are at the intersection of Systems and Networking and Embedded Systems, and he is particularly excited about research problems that benefit from using hardware insights to build more scalable and energy efficient systems. In recent years, his work has focused on Green Computing, Mobile Computing and Energy Efficient Buildings. Agarwal has a BE in Electrical Engineering from Pune University in India, an MS in Information and Computer Science from University of California at Irvine, and a PhD in Computer Engineering from the University of California at San Diego. He is a member of the IEEE, ACM and USENIX.
- Steven Wu is an Assistant Professor in the School of Computer Science at Carnegie Mellon University, with an appointment in the Institute for Software Research (in the Societal Computing program), and affiliated appointments with the Machine Learning Department and the Human-Computer Interaction Institute. He received a Ph.D. in Computer Science from the University of Pennsylvania, where he was co-advised by Michael Kearns and Aaron Roth. His doctoral dissertation received Penn's Morris and Dorothy Rubinoff Award for the best thesis. He is a recipient of an Amazon Research Award, a Google Faculty Research Award, a J.P. Morgan Faculty Award, a Facebook Research Award, and a Mozilla Research Grant. Before CMU, he was an Assistant Professor of Computer Science & Engineering at the University of Minnesota. Before that, he spent a year as a post-doctoral researcher at Microsoft Research-New York City in the Machine Learning and Algorithmic Economics groups.
► Professors David Garlan and Ehab Al-Shaer — Adaptive Intrusion Mitigation and Tolerance for IIOT systems
→ Due to complex attack surfaces in IIOT systems, relying only on prevention and detection is inadequate for protection these systems. Dynamic real-time mitigation of active attacks and adaptive graceful degradation are important defense capabilities to manage risk while maintaining functionality. One of our goals in this project is to dynamically create a course of actions (CoA) to block or deceive the attackers from reaching their goals during their progress in the kill/attack chain (a sequence of attack techniques). The CoA can be determined by predicting potential attack chains and their technique composition based on potential attack chains. To address the challenge of large space of attack scenario and incomplete knowledge of the attack chains, our approach integrates both RL and SMT to quickly identify the potential attack chains and determine the optimal cost-effective mitigation. In addition, systems under attack should be able to gracefully degrade to manage risk while maintaining functionality in an uncertain environment. Current approaches to system security evaluation do not enable this. We can circumvent this uncertainty and still effectively manage risk to create and automate adaptable, secure systems facing attack though the use of formal methods to evaluate system architectures, achieving (1) graceful degradation capability at design-time and (2) graceful degradation while under attack at run-time.
- David Garlan is a professor of Computer Science and Associate Dean in the School of Computer Science at Carnegie Mellon University. His research interests include software architecture, self-adaptive and self-securing systems, formal methods, and cyber-physical systems. He is recognized as one of the founders of the field of software architecture, and, in particular, formal representation and analysis of architectural designs. He has received a Stevens Award Citation for “fundamental contributions to the development and understanding of software architecture as a discipline in software engineering,” an Outstanding Research award from ACM SIGSOFT for “significant and lasting software engineering research contributions through the development and promotion of software architecture,” an Allen Newell Award for Research Excellence, an IEEE TCSE Distinguished Education Award, and a Nancy Mead Award for Excellence in Software Engineering Education. He is a Fellow of the IEEE and ACM.
- Dr. Ehab Al-Shaer is a Distinguished Research Fellow at ISR, and Faculty Member of CyLab at Carnegie Mellon University. Dr. Al-Shaer has more than two decades as a researcher and educators in the field of Cybersecurity. Prior joining CMU, Dr. Al-Shaer was Professor and the Founding Director of CyberDNA and NSF Cybersecurity Analytics and Automation (CCAA) centers in the University of North Carolina Charlotte from 2009-2020. His area of research expertise includes formal methods for security configuration verification, synthesis and hardening of enterprise, SDN, IoT and smart grid systems, adaptive & automated cyber defense for cyber resilience, attack deterrence and deception. He was designated by the Department of Defense (DoD) as a Subject Matter Expert (SME) on security analytics and automation in 2011, and he was awarded the IBM Faculty Award in 2012, and UNC Charlotte Faculty Research Award in 2013. Dr. Al-Shaer was the chair of ARO Autonomous Cyber Deception Workshop in 2018, General Chair of ACM Computer and Communication in 2009 and 2010, the chair of NSF Workshop in Assurable and Usable Security Configuration in 2008. Dr. Al-Shaer has also been a Program Committee Chair and TPC member for many conferences in his area.
Zoom Participation. See announcement.