Keynote and Invited Talks - AIPR 2020

Biographies and Abstracts (where available)


sajal das

Sajal K. Das (IEEE Fellow)

Professor and Daniel St. Clair Endowed Chair, Department of Computer Science

Missouri University of Science and Technology, USA

Title: Securing Cyber-Physical and IoT Systems in Smart Living Environments

Time: October 13th from 9am - 9:50am EDT

Abstract: Our daily lives are becoming increasingly dependent on a variety of smart cyber-physical infrastructures, such as smart cities and buildings, smart energy grid, smart transportation, smart healthcare, etc. Alongside, smartphones and sensor-based IoTs are empowering humans with fine-grained information and opinion collection through crowdsensing about events of interest, resulting in actionable inferences and decisions. This synergy has led to the cyber-physical-social (CPS) convergence with human in the loop, the goal of which is to improve the “quality” of life. However, CPS and IoT systems are extremely vulnerable to failures, attacks and security threats.

This talk will highlight unique research challenges in securing such systems, followed by novel defense mechanisms. Our proposed frameworks and solutions are based on a rich set of theoretical and practical design principles, such as secure data fusion, uncertainty reasoning, information theory, prospect theory, reputation scoring, and belief and trust models. Two case studies will be considered: (1) Security forensics and lightweight statistical anomaly detection in the smart grid CPS to defend against organized and persistent adversaries that can launch data falsification attacks on the smart meters using stealthy strategies. The novelty of our approach lies in a newly defined information-theoretic metric that helps quantify robustness and security, thus minimizing the attacker’s impact on the customers and utilities with low false alarm rates; (2) Secure and trustworthy decision making in mobile crowd sensing to detect false (or spam) contributions due to selfish and malicious behavior of users. Based on the cumulative prospect theory and reputation/trust model, our approach prevents revenue loss owing to undue incentives and improves the operational reliability and decision accuracy. The talk will be concluded with directions for future research.

Biography: Dr. Sajal K. Das, whose academic genealogy includes Thomas Alva Edison, is a professor of Computer Science and the Daniel St. Clair Endowed Chair at Missouri University of Science and Technology, where he was the Chair of Computer Science during 2013-2017. Prior to 2013, he was a University Distinguished Scholar Professor of Computer Science and Engineering, and founding director of the Center for Research in Wireless Mobility and Networking at the University of Texas at Arlington. During 2008-2011, Dr. Das served the National Science Foundation as a Program Director in the Computer and Network Systems Division. His research interests include wireless sensor networks, mobile and pervasive computing, smart environments (smart city, smart grid, smart healthcare), cyber-physical systems; IoT, crowdsensing, cloud computing, security and trustworthiness, social and biological networks, and applied graph theory and game theory. He has contributed significantly to these areas, having published 300+ research articles in high quality journals and 400+ papers in peer-reviewed conferences, and 52 book chapters. A holder of 5 US patents, Dr. Das has directed numerous funded projects totaling over $16 million and coauthored four books – Smart Environments: Technology, Protocols, and Applications (John Wiley, 2005); Handbook on Securing Cyber-Physical Critical Infrastructure: Foundations and Challenges (Morgan Kaufman, 2012); Mobile Agents in Distributed Computing and Networking (Wiley, 2012); and Principles of Cyber-Physical Systems: An Interdisciplinary Approach (Cambridge University Press, 2020). According to DBLP, Dr. Das is one of the most prolific authors in computer science. His h-index is 86 with 33,000+ citations according to Google Scholar. He is the founding Editor-in-Chief of Elsevier’s Pervasive and Mobile Computing journal, and serves as an Associate Editor of several journals including the IEEE Transactions on Mobile Computing, IEEE Transactions on Dependable and Secure Computing, and ACM Transactions on Sensor Networks. A founder of IEEE PerCom, WoWMoM, SMARTCOMP and ICDCN conferences, Dr. Das served as General and Program Chair of numerous conferences. He is a recipient of 10 Best Paper Awards in prestigious conferences, and numerous awards for teaching, mentoring and research including IEEE Computer Society’s Technical Achievement award for pioneering contributions to sensor networks and mobile computing, and University of Missouri System President’s Award for Sustained Career Excellence. He graduated 43 PhD, 32 MS thesis students, and 9 postdoctoral fellows. Dr. Das is an IEEE Fellow.



sajal das

Lujo Bauer (Professor, Carnegie Mellon University)

Title: On Evasion Attacks against Machine Learning in Practical Settings

Time: October 13th from 1pm - 1:50pm EDT

Abstract: Much research over the past decade has shown that machine learning algorithms are susceptible to adversarial examples---carefully crafted, minimal perturbations to training-time inputs that lead to misclassification at test time. The majority of such research, however, has been carried out with toy datasets such as MNIST and without consideration for practical constraints that need to be overcome when attacking a real-world system. In this talk I'll examine two real-world uses of machine learning algorithms---for face recognition and for malware classification. I'll describe the constraints that attacks on these systems would have to overcome in practice, and I'll show that overcoming these constraints is, unfortunately, well within attackers' capabilities.

Biography: Lujo Bauer is a Professor of Electrical and Computer Engineering, and of Computer Science, at Carnegie Mellon University. He received his B.S. in Computer Science from Yale University in 1997 and his Ph.D., also in Computer Science, from Princeton University in 2003. Dr. Bauer is a member of CyLab, Carnegie Mellon's computer security and privacy institute, and serves as the director of CyLab's Cyber Autonomy Research Center. Dr. Bauer's research examines many aspects of computer security and privacy, including developing high-assurance access-control systems, building systems in which usability and security co-exist, and designing practical tools for identifying software vulnerabilities. His recent work focuses on developing tools and guidance to help users stay safer online and on examining how advances in machine learning can (or might not) lead to a more secure future. Dr. Bauer served as the program chair for the flagship computer security conferences of the IEEE (S&P 2015) and the Internet Society (NDSS 2014) and is an associate editor of ACM Transactions on Privacy and Security.



rudra dutta

Rudra Dutta (Senior Member of IEEE; Distinguished Member of ACM)

Professor, North Carolina State University

Title: AERPAW: A Unique Research Platform for Advanced Wireless Communications and Networking

Time: October 14th from 9am - 9:50am EDT

Abstract: The Aerial Experimentation and Research Platform for Advanced Wireless (AERPAW) facility, in early design and construction at the Centennial Campus of North Carolina State University and adjoining areas in the City of Raleigh and the Town of Cary, is planned to be a wireless testbed embedded in the real world, initially spanning an area of a few square miles that contains urban, suburban, and agricultural landforms.  The experimental facilities will consist of a variety of radio resources (including programmable software-defined radios), installed semi-permanently at over 30 locations, and over 20 portable nodes, with the portable nodes being mountable on a variety of vehicles, including ground and aerial robots whose trajectory can be programmatically controlled.  We expect that it will enable a rich variety of wireless research experiments with a high degree of realism, many of which would be impossible without such a facility.  This talk will briefly describe the architecture and design of AERPAW, and the experiment scenarios that we envision AERPAW will be able to house.

Biography: Rudra Dutta received a B.E. in Electrical Engineering from Jadavpur University, Kolkata, India, in 1991, a M.E. in Systems Science and Automation from Indian Institute of Science, Bangalore, India in 1993, and a Ph.D. in Computer Science from North Carolina State University, Raleigh, USA, in 2001. From 1993 to 1997 he worked for IBM as a software developer and programmer in various networking related projects. He has been employed from 2001 - 2007 as Assistant Professor, from 2007 - 2013 as Associate Professor, and since 2013 as Professor, in the department of Computer Science at the North Carolina State University, Raleigh. As of Fall, 2018, he is serving as Associate Department Head on an interim basis. His current research interests focus on design and performance optimization of large networking systems, Internet architecture, wireless networks, and network analytics. He is a senior member of IEEE and a distinguished member (distinguished engineer) of ACM. His work has been supported by grants from the National Science Foundation, the Army Research Office, the National Security Agency, and industry, most recently including a PAWR grant from NSF (the AERPAW project). He has served as a reviewer for many premium journals, on NSF, DoE, ARO, and NSERC (Canada) review panels, as part of the organizing committee of many premium conferences, most recently as General Co-Chair for the IEEE Sarnoff Symposium in 2019. He previously served on the editorial boards of the Elsevier Journal of Optical Switching and Networking, and the Springer Photonic Communication Networks journal, for several years, and is currently serving as Program Co-Chair of the Optical Networking Symposium at IEEE Globecom 2021.



anita nikolich

Anita Nikolich

Research Scientist at UIUC

Title: FABRIC: More than Just a Pretty Testbed

Time: October 14th from 1pm - 1:50pm EDT

Abstract: FABRIC creates a unique research infrastructure to enable cutting-edge, at-scale research in networking, cybersecurity, distributed computing and storage, machine learning and AI. We are crafting a rich tapestry of ‘everywhere-programmable’ global nodes equipped with large amounts of network, compute and storage, interconnected by high speed, dedicated optical links connecting FABRIC to specialized testbeds (5G/IoT PAWR, NSF Clouds), HPC, science facilities and the Internet. I’ll give a high-level introduction to FABRIC and some thoughts about the types of ‘out of the box’ security and machine learning experiments we’d like the community to consider.

Biography: Anita is a Research Scientist at UIUC, Cyber Policy Fellow at the University of Chicago, Co-Director of the DEFCON AI Village and a security consultant at a cryptocurrency exchange.



nitin vaidya

Nitin Vaidya (IEEE Fellow)

Professor and McDevitt Chair of Computer Science, Georgetown University

Title: Security and Privacy for Distributed Optimization and Learning

Time: October 15th from 9am - 9:50am EDT

Abstract: Consider a network of agents wherein each agent has a private cost function. In the context of distributed machine learning, the private cost function of an agent may represent the “loss function” corresponding to the agent’s local data. The objective here is to identify parameters that minimize the total cost over all the agents. In machine learning for classification, the cost function is designed such that minimizing the cost function should result in model parameters that achieve higher accuracy of classification. Similar optimization problems arise in the context of other applications as well.

Our work addresses privacy and security of distributed optimization with applications to machine learning. In privacy-preserving machine learning, the goal is to optimize the model parameters correctly while preserving the privacy of each agent’s local data. In security, the goal is to identify the model parameters correctly while tolerating adversarial agents that may be supplying incorrect information. When a large number of agents participate in distributed optimization, security compromise or failure of some of the agents becomes increasingly likely. The talk will provide intuition behind the design and correctness of the algorithms.

Biography: Nitin Vaidya is the McDevitt Chair of Computer Science at Georgetown University. He received his Ph.D. from the University of Massachusetts at Amherst. He previously served as a Professor and Associate Head in Electrical and Computer Engineering at the University of Illinois at Urbana-Champaign. He has co-authored papers that received awards at several conferences, including 2015 SSS, 2007 ACM MobiHoc and 1998 ACM MobiCom. He is a fellow of the IEEE. He has served as the Chair of the Steering Committee for the ACM PODC conference, as the Editor-in-Chief for the IEEE Transactions on Mobile Computing, and as the Editor-in-Chief for ACM SIGMOBILE publication MC2R.


nitin vaidya

Prabha Balakrishnan (IEEE Senior Member)

Program Director in the Human Centered Computing (HCC) program of Information and Intelligent Systems (IIS), Division of the CISE (Computer and Information Science and Engineering) Directorate of the National Science Foundation (NSF) & Professor, Computer Science Department, University of Texas at Dallas

Title: Trusted Computing, Privacy, and Securing Multimedia: A Perspective from the National Science Foundation (NSF)

Time: October 15th from 1pm - 1:50pm EDT

Abstract: This talk starts off with a brief background on Prabhakaran’s personal research in multimedia media forensics, using watermarking and other related approaches using machine learning. He primarily dealt with tamper proofing and authentication of 3D data: 3D meshes, 3D point clouds, and 3D human motion capture data.  Based on these research results, Prabhakaran and his research team designed ALERT (Authentication, Localization, and Estimation of Risks and Threats), as a secure layer in the decision support system used in the navigation control of vehicles and robots. His current research includes exploration of deep learning techniques for tamper detection in 3D data.

With this research background, Prabhakaran has been involved National Science Foundation (NSF) programs such as Human Centered Computing (HCC) and Secure and Trustworthy Computing (SaTC). He is also involved with Fairness in Artificial Intelligence (AI), Future of Work, Smart and Connected Communities. The talk will provide an overview of NSF’s leadership in AI and NSF CISE (Computer and Information Science and Engineering) Directorate’s activities on Secure and Trustworthy Computing.

Biography: Prabha (Balakrishnan) Prabhakaran is currently a Program Director in the Human Centered Computing (HCC) program of Information and Intelligent Systems (IIS) Division of the CISE (Computer and Information Science and Engineering) Directorate of the National Science Foundation (NSF). He is also involved with Secure and Trustworthy Computing as well as other programs such as Fairness in Artificial Intelligence, Future of Work. He is also a Professor in the faculty of Computer Science Department, University of Texas at Dallas. Dr. Prabhakaran received the prestigious NSF CAREER Award FY 2003 for his proposal on Animation Databases. He was selected as an ACM Distinguished Scientist in 2011 and is currently an IEEE Senior Member. He is an Associate Editor of IEEE Transactions on Multimedia. He is Member of the Editorial board of Multimedia Systems Journal (Springer), Multimedia Tools and Applications journal (Springer), and other multimedia systems journals. He received the Best Associate Editor for 2015, from Springer’s Multimedia Systems Journal. Dr Prabhakaran is a Member of the Executive Council of the ACM Special Interest Group on Multimedia (SIGMM) and is the Co-Chair of IEEE Technical Committee on Multimedia Computing (TCMC) Special Interest Group on Video Analytics (SIGVA). Dr. Prabhakaran served the General Co-Chair of the IEEE International Conference on Health Informatics (ICHI) 2015. He was also a General Co-Chair of ACM International Conference on Multimedia Retrieval 2013 (ICMR 2013), IEEE Haptic, Audio, and Visual Environments (HAVE) 2014, a General Co-chair of ACM Multimedia 2011, and ACM Multimedia and Security (MM&Sec) 2007. Prof Prabhakaran's research has been funded by Federal Agencies such as the National Science Foundation (NSF), USA Army Research Office (ARO), and the US-IGNITE Program, apart from industries and consortiums.