The Metaverse and Its Cybersecurity Challenges

Abstract: The Metaverse can be envisioned as a 3D immersive virtual world, where people can use Augmented/Virtual Reality (AR/VR) devices to access and interact with others through digital avatars. The Metaverse faces various security risks inherited from its predecessor and new specialized threats. It is challenging to mitigate and tackle these issues in a large-scale setting with numerous wearable devices such as IoT devices, augmented, virtual reality (AR/VR) headsets and the participation of various stakeholders from both physical and virtual worlds. In this seminar, we will first provide some background of the Metaverse. Then, we will describe how the blockchain and machine learning (ML) techniques can allow us to engineer building blocks and functions of the Metaverse including its economic/financial systems, metaverse governance, identity and authentication management, data and digital asset managements, machine learning based intrusion/anomaly detection systems. We then introduce a layer-based architecture of the Metaverse, discuss potential security threats and countermeasures for the Metaverse. Finally, we share our recent research findings in the Metaverse security in which advanced blockchain and ML techniques are employed to develop the Metaverse digital asset management and intrusion detection systems.

Professor Long Le, IEEE Fellow Institut National De La Recherche Scientifique (INRS) Énergie Matériaux Télécommunications Research Centre University of Quebec 800 de la Gauchetière West, Suite 6900 Montreal, Canada H5A 1K6

Brief Bio: Dr. Long Le is currently a full professor at INRS, University of Quebec. He received his PhD degree from University of Manitoba in 2007. Prior to joining INRS, he was a postdoctoral researcher at Massachusetts Institute of Technology in 2008-2010 and University of Waterloo in 2007-2008. Dr. Le leads the NECPHY-Lab performing research and training in the broad areas of wireless communications, networking, edge/cloud computing, smartgrids and the Metaverse. Dr. Le is the co-authors of 2 books and more than 240 articles, mostly published on top IEEE journals and conferences. He has served as an editor for different journals including IEEE Transactions on Communications (2022-present), IEEE Transactions on Cognitive Communications and Networking (2021-present), IEEE Transactions on Wireless Communications, IEEE Wireless Communications Letters, and IEEE Communications Surveys & Tutorials. He has served in the organization committees for different conferences including IEEE WCNC, IEEE VTC, and IEEE PIMRC. Dr. Le is an IEEE Fellow.

Scalable Multicast Transmission for 6G with Enhanced Computation-Communication Efficiency

Abstract: Next-generation wireless systems are anticipated to feature extremely large-scale antenna arrays to enable immersive and massive communication. For such systems to be practical, transmission solutions must be ultra-low-complexity and highly scalable. In particular, multicast transmission techniques at the physical layer can effectively support massive data distribution and access in mobile broadband, edge computing, distributed learning, and the Internet of Things applications. However, the highly complex computational methods and the communication costs of centralized processing architecture pose significant challenges. In this talk, we will first share our recent results on the optimal downlink multicast beamforming, highlighting how its structural properties can lead to highly scalable algorithm solutions. We will then discuss coordinated multicast transmission in multi-cell networks and present a highly scalable solution combined with a semi-distributed computing approach, resulting in orders of magnitude of savings in computation and communication for multi-cell coordination.

Professor Min Dong, IEEE Fellow Department of Electrical, Computer and Software Engineering Ontario Tech University 2000 Simcoe St. N., Oshawa, Ontario L1G 0C5, Canada

Brief Bio: Min Dong is a Professor in the Department of Electrical, Computer and Software Engineering at Ontario Tech University. She received the Ph.D. degree in electrical and computer engineering from Cornell University in 2004. From 2004 to 2008, she was with Qualcomm Inc., San Diego, CA. Her research interests include wireless communications, statistical signal processing, learning techniques, optimization and control applications in cyber-physical systems. She received the 2004 IEEE Signal Processing Society Best Paper Award and a Best Paper Award at IEEE ICCC 2012. She is a co-author of the Best Student Paper at IEEE SPAWC 2021 and the Best Student Paper of Signal Processing for Communications and Networking at IEEE ICASSP 2016. She is a Senior Area Editor for IEEE Transactions on Signal Processing. She served on the Steering Committee of IEEE Transactions on Mobile Computing (2019-2021) and was an elected member of the Signal Processing for Communications and Networking (SP-COM) Technical Committee of IEEE Signal Processing Society (2013-2018). She also served on the editorial boards of IEEE Transactions on Wireless Communication and IEEE Signal Processing Letters. She is a Fellow of IEEE.

Batteryless Internet of Things with Backscatter Radio

Abstract: Backscatter radio lies at the heart of commercial, batteryless radio frequency identification (RFID) tags and has recently attracted significant research interest. Backscatter radio is grounded on RF reflection principles that simplify communicator design to a single switch, connected to an antenna, offering ultra-low power consumption per tag, at the expense of reduced communication range and coverage. Bistatic or multistatic architectures, where illuminator and receiver of the tag-backscattered information are placed at distant locations, have been proposed to extend range and coverage, compared to conventional monostatic, at the expense of increased (installation) cost. In this talk, a distributed, real-time (less than 0.5msec latency), near-optimal, noncoherent sequence detection technique will be presented, tailored to the Miller line coding of commercial RFIDs and tested, with commercial, off-the-self, software-defined radios (SDR), connected over Ethernet. Experimental results show that doubling the number of transmitting antennas can roughly double indoor coverage, compared to the (commercial) monostatic architecture, allowing for scalable, low-cost RFID interrogation in warehouses. Work on cm-accuracy RFID tag indoor localization with a mobile robot, will also be shown. Next, design and implementation of a batteryless, RF-powered, reconfigurable intelligent surface (RIS) using RFIDs, perhaps the first of its kind, will be presented.

Professor Aggelos Bletsas, IEEE Fellow WINLAB & Dept. of ECE, Rutgers University New Brunswick, NJ 08901

Brief Bio: Aggelos Bletsas (IEEE Fellow) received the Diploma degree (Hons.) in Electrical and Computer Engineering from the Aristotle University of Thessaloniki, Greece, in 1998, and the M.Sc. and Ph.D. degrees in Media Arts & Sciences (Media Lab) from the Massachusetts Institute of Technology (MIT), Cambridge, MA, USA, in 2001 and 2005, respectively. He has worked with Mitsubishi Electric Research Laboratories (MERL), Cambridge, MA, USA and the RadioCommunications Laboratory (RCL), Department of Physics, Aristotle University of Thessaloniki, Greece. From 2009 until December of 2023, he served a faculty at the the School of Electrical and Computer Engineering, Technical University of Crete, Greece. In Jan. of 2024 he joined as Full Professor WINLAB and the Dept. of ECE, Rutgers University. Prof. Bletsas is currently 2022-2024 IEEE Communications Society (ComSoc) Distinguished Lecturer and 2023-2025 IEEE RFID Council (CRFID) Distinguished Lecturer. He was co-recipient of the IEEE Communications Society (ComSoc) 2008 Marconi Prize Paper Award in Wireless Communications, and various Best (Student) Paper Awards, e.g., in IEEE RFID-TA 2011, IEEE ICASSP 2015, IEEE RFID-TA 2017, MOCAST 2018 and IEEE WCNEE 2021. One of his articles is being regularly ranked 1st (for several years) in Google Scholar Classic Papers in Computer Networks and Wireless Communication.

Hosts

Dr. Arijit Roy Assistant Professor Department of Computer Science and Engineering Indian Institute of Technology Patna, India Website: https://arijit-iitkgp.github.io

Dr. Ayan Mondal Assistant Professor Department of Computer Science and Engineering Indian Institute of Technology Indore Khandwa Road, Simrol, Indore 453552, India Website: https://www.iiti.ac.in/people/~ayanm/

Prrofessor Sudip Misra, PhD, FIEEE, FNAE, FNASc, FIET, FBCS, FRSPH, FIETE ACM Distinguished Member Alexander von Humboldt Fellow (Germany) IEEE Communications Society Distinguished Lecturer Professor & INAE Abdul Kalam Technology Innovation National Fellow Department of Computer Science & Engineering Indian Institute of Technology Kharagpur-721302 West Bengal, India Official Website: https://cse.iitkgp.ac.in/~smisra/ SWAN Group: https://cse.iitkgp.ac.in/~smisra/swan/