Title: Federated Learning in Unreliable and Resource-Constrained Cellular Wireless Networks

Date: May 26, 2021; Time: 11AM EDT

Registration: Please register at https://albany.zoom.us/meeting/register/tJYvd-irrDMuH9ImDFQ65_9LugOGR4J-fEBg

Abstract: Federated learning is a machine learning setting where the centralized location trains a learning model by using remote devices. Federated learning algorithms cannot be employed in wireless networks unless the unreliable and resource-constrained nature of the wireless medium is taken into account. In this talk, I shall present a federated learning algorithm that is suitable for cellular wireless networks in a real-world scenario. I shall discuss its convergence properties, and the effects of local computation steps and communication steps on its convergence. Through experiments on real and synthetic datasets, I shall demonstrate the convergence of the proposed algorithm.

Bio: Ekram Hossain (IEEE Fellow) is a Professor in the Department of Electrical and Computer Engineering at University of Manitoba, Winnipeg, Canada. He is a Member (Class of 2016) of the College of the Royal Society of Canada, a Fellow of the Canadian Academy of Engineering, and also a Fellow of the Engineering Institute of Canada (http://home.cc.umanitoba.ca/~hossaina). He received his Ph.D. in Electrical Engineering from University of Victoria, Canada, in 2001. Dr. Hossain’s current research interests include design, analysis, and optimization of wireless communication networks (with emphasis on beyond 5G/6G cellular), applied machine learning and game theory, and network economics. He was elevated to an IEEE Fellow “for contributions to spectrum management and resource allocation in cognitive and cellular radio networks”. He was listed as a Clarivate Analytics Highly Cited Researcher in Computer Science in 2017, 2018, 2019, and 2020. Dr. Hossain has won several research awards including the “2017 IEEE Communications Society Best Survey Paper Award, the 2011 IEEE Communications Society Fred Ellersick Prize Paper Award, University of Manitoba Merit Award in 2010, 2013, 2014, and 2015 (for Research and Scholarly Activities), and the IEEE Wireless Communications and Networking Conference 2012 (WCNC’12) Best Paper Award. He received the 2017 IEEE ComSoc TCGCC (Technical Committee on Green Communications & Computing) Distinguished Technical Achievement Recognition Award “for outstanding technical leadership and achievement in green wireless communications and networking”. Currently he serves as the Editor-in-Chief of the IEEE Press and an Editor for IEEE Transactions on Mobile Computing. Previously, he served as an Area Editor for the IEEE Transactions on Wireless Communications in the area of “Resource Management and Multiple Access” (2009-2011) and an Editor for the IEEE Journal on Selected Areas in Communications – Cognitive Radio Series (2011-2014). He serves as the Director of Magazines for the IEEE Communications Society (2020-2021). Dr. Hossain was an elected Member of the Board of Governors of the IEEE Communications Society for the term 2018-2020. He is a Distinguished Lecturer of the IEEE Communications Society. He is a registered Professional Engineer in the province of Manitoba, Canada.

About the Monthly Virtual Seminar Series: The IEEE TCCN Special Interest Group for AI and Machine Learning in Security conducts a monthly virtual seminar series to highlight the challenges in securing the next generation (xG) wireless networks. The talks will feature cutting edge research addressing both technical and policy issues to advance the state-of-the-art in security techniques, architectures, and algorithms for wireless communications.

Title: Secure Code Execution on Untrusted Remote Devices

Date: April 28, 2021; Time: 1PM EDT

Registration: Please register using the following link. You will receive a link in your email to attend the talk online.
https://forms.gle/bTah3LEyV5vUxMAw7

Abstract: Our society is increasingly reliant upon a wide range of Cyber-Physical Systems (CPS), Internet-of-Things (IoT), embedded, and so-called “smart” devices. They often perform safety-critical functions in numerous settings, e.g., home, office, medical, automotive and industrial. Some devices are small, cheap and specialized sensors and/or actuators. They tend to have meager resources, run simple software, sometimes upon “bare metal”. If such devices are left unprotected, consequences of forged sensor readings or ignored actuation commands can be catastrophic, particularly, in safety-critical settings. This prompts the following three questions: (1) How to trust data produced by a simple remote embedded device? (2) How to ascertain that this data was produced via execution of expected software? And, (3) Is it possible to attain (1) and (2) under the assumption that all software on the remote device might be modified or compromised? In this talk, we answer these questions by describing APEX: (Verified) Architecture for Proofs of Execution, the first of its kind result for low-end embedded systems. This work has a range of applications, especially, to authenticated sensing and trustworthy actuation, APEX incurs low overhead, making it affordable even for lowest-end embedded devices; it is also publicly available.

Bio: Gene Tsudik is a Distinguished Professor of Computer Science at the University of California, Irvine (UCI). He obtained his PhD in Computer Science from USC in 1991. Before coming to UCI in 2000, he was at the IBM Zurich Research Laboratory (1991-1996) and USC/ISI (1996-2000). His research interests include many topics in security, privacy and applied cryptography. Gene Tsudik is a Fulbright Scholar, Fulbright Specialist (twice), a fellow of ACM, IEEE, AAAS, IFIP and a foreign member of Academia Europaea. From 2009 to 2015 he served as Editor-in-Chief of ACM Transactions on Information and Systems Security (TISSEC, renamed TOPS in 2016). Gene was the recipient of 2017 ACM SIGSAC Outstanding Contribution Award. He is also the author of the first crypto-poem published as a refereed paper.

About the Monthly Virtual Seminar Series:

The IEEE TCCN Security Special Interest Group conducts a monthly virtual seminar series to highlight the challenges in securing the next generation (xG) wireless networks. The talks will feature cutting edge research addressing both technical and policy issues to advance the state-of-the-art in security techniques, architectures, and algorithms for wireless communications.

Title: Adversarial Machine Learning for Wireless Security in 5G and Beyond

Date and Time: March 26, 2021 at 10AM ET

Registration Process: Please register using the following link. You will receive a link in your email to attend the talk online.

https://forms.gle/krrmynfr3DDH7ENS9

Abstract: Machine learning provides powerful means to learn from the dynamic spectrum environment and solve complex tasks for wireless communications. Supported by recent advances in algorithmic and computational capabilities, deep learning has emerged as a viable solution to efficiently utilize the limited spectrum resources and optimize wireless communications, with 5G and beyond enhancements to meet the ever-growing demands for high-rate and low-latency communications. As deep learning is becoming a key component in emerging wireless technologies, a new security threat arises due to adversarial machine learning that exploits the vulnerabilities of deep learning to adversarial manipulations. Adversarial machine learning has been applied to different data domains ranging from computer vision to natural language processing. By considering the unique characteristics of the wireless medium, this talk will present adversarial machine learning as a new attack surface for the next-generation communication systems. Novel attack and defense mechanisms built upon adversarial machine learning will be described with examples from signal classification, dynamic spectrum access, and 5G and beyond applications related to spectrum co-existence, user authentication, covert communications, and network slicing. Research challenges and directions will be discussed for effective and safe adoption of much-needed machine learning techniques in the emerging wireless technologies.

Bio: Dr. Yalin Sagduyu is the Director of Networks and Security Division at Intelligent Automation, Inc. (IAI). He received his Ph.D. degree in Electrical and Computer Engineering from University of Maryland, College Park. At IAI, he directs a division of over 50 research scientists and engineers, and executes a broad portfolio of R&D projects on wireless communications, networks, security, machine learning, adversarial machine learning, and 5G and beyond. He has been a Visiting Research Professor in the Electrical and Computer Engineering Department of University of Maryland, College Park. He served as a Conference Track Chair at IEEE PIMRC, IEEE GlobalSIP and IEEE MILCOM, and in the organizing committee of IEEE GLOBECOM. He organized and chaired workshops at IEEE CNS, IEEE ICNP, ACM Mobicom, and ACM WiSec. He received the Best Paper Award at IEEE HST.

About the Monthly Virtual Seminar Series:

The IEEE TCCN Security Special Interest Group conducts a monthly virtual seminar series to highlight the challenges in securing the next generation (xG) wireless networks. The talks will feature cutting edge research addressing both technical and policy issues to advance the state-of-the-art in security techniques, architectures, and algorithms for wireless communications.

Title: A Quick Look at New Risks Facing Wireless Systems

Date and Time: February 25, 2021 at 10AM ET

Registration Process: Please register using the following link. You will receive a link in your email to attend the talk online.

https://forms.gle/omTft4DCuuGVtdDz7

Abstract: Wireless networks are susceptible to a wide range of security risks. The evolution from old wireless technologies, such as3G and 802.11, to newer technologies, such as 5G and mmWave, hasnot fundamentally changed the core challenges that undermines the security of wireless networks: Wireless systems are easy to access,the wireless medium is easy to broadcast and eavesdrop on, and the increasingly pervasive nature means that we are becoming increasingly reliant on them for day-to-day functions. This talk will examine a broad sampling of wireless-based threats that will likely become more prevalent as we move towards the next generation of wireless system. These systems are characterized by a closer integration between communications, computation, and the real world. As such, the challenges we face to secure these systems requires that wireless engineers and systems developers think more holistically about how they will design and implement security mechanisms. In short, we must really work to protect our systems “across the stack” and even “into the application.”

Bio: Wade Trappe is a Professor in the Electrical and Computer Engineering Department at Rutgers University, and Associate Director of the Wireless Information Network Laboratory (WINLAB), where he directs WINLAB’s research in wireless security. He has led several federally funded projects in the area of cybersecurity and communication systems, projects involving security and privacy for sensor networks, physical layer security for wireless systems, a security framework for cognitive radios, the development of wireless testbed resources (the ORBIT testbed, www.orbit-lab.org), and new RFID technologies. He was the principal investigator for the original DARPA Spectrum Challenge, in which teams battled for spectrum superiority against each other on the ORBIT testbed arena. His experience in network security and wireless spans over 20 years, and he has co-authored a popular textbook in security, Introduction to Cryptography with Coding Theory, as well as several monographs on wireless security, including Securing Wireless Communications at the Physical Layer and Securing Emerging Wireless Systems: Lower-layer Approaches.

About the Monthly Virtual Seminar Series:

The IEEE TCCN Security Special Interest Group conducts a monthly virtual seminar series to highlight the challenges in securing the next generation (xG) wireless networks. The talks will feature cutting edge research addressing both technical and policy issues to advance the state-of-the-art in security techniques, architectures, and algorithms for wireless communications.