Title: Securing and Optimizing Wireless Systems with AI-Native & Data-Driven Wireless Signal Processing in the Physical Layer

Date and Time: December 13, 2022 at 10 AM ET

Registration Process: Please register at https://tinyurl.com/38s8vxuc

Abstract: This talk will provide an overview of ways in which machine learning and data-driven signal processing are impacting wireless sensing systems, spectrum anomaly-detection and analytic systems, and leading to powerful spectrum awareness capabilities which help to provide security, monitoring, and adaptation tools never previously possible at scale in wireless systems. We’ll talk about some of the work we’ve done at both DeepSig and VT to enable this, highlighting several works which illustrate how AI/ML based edge processing provide valuable security tools which fill significant gaps in the wireless threat surface which were previously prohibitive or highly manual and labor intensive to address. We’ll show some examples of how these approaches can be rapidly adopted from applied research into fieldable commercial systems, and considering their potential impact in securing and optimizing future wireless systems. Finally, we’ll also consider the impact of data driven baseband processing for wireless transmission and reception – The concept of an AI-Native Air Interface – often in a form resembling a channel autoencoder, presents a powerful tool for optimizing physical layer waveforms for hardening against a wide range of wireless threats and failure modes. We’ll highlight some of our work as well as others in this area, and consider where this can help optimize wireless security and resilience in communications systems in the future. Finally, we’ll consider future areas for research, industry adoption of techniques, and potentially transformative wireless security trends going forward.

Bio: Tim O’Shea is the CTO and Co-Founder at DeepSig Inc and a Research Assistant Professor at Virginia Tech in Arlington, VA. He is focused on building machine learning and AI-Native wireless baseband processing capabilities to enhance the spectral and energy performance of 5G, 5G-Advanced, and 6G wireless air interfaces, and leveraging AI-Driven spectral and spatial channel awareness and sensing to optimize multi-user and multi-access next generation wireless systems. Previously he worked with wireless startups Hawkeye 360 and Federated Wireless in seed stage and held engineering R&D positions with both the US DOD and with Cisco Systems. He is the author of over 50 peer reviewed works and patents in the machine learning for communications space, and is involved in IEEE COMSOC, IEEE MLC ETI, Next-G Alliance, and OpenRAN efforts to accelerate AI driven communications systems and their adoption within next generation RAN and Open-vRAN.

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.