Alan (Zaoxing) Liu
Assistant Professor (ECE, CS)
- Title Assistant Professor (ECE, CS)
- Office 8 St. Mary’s St, Room 335
- Email firstname.lastname@example.org
- Education PhD, Johns Hopkins University, 2018
- Networked Systems
- Programmable Networks
- Big Data Analytics
- Cloud Computing
- Network Security
Recent Research Projects:
Future-Proof, Trustworthy Telemetry: Emerging networked applications, such as cloud gaming or cloud streamed augmented reality, are expected to further stress both control systems and network monitoring by requiring real-time response to rapid changes in traffic workloads. This project aims to address the needs of future network control by enabling a network telemetry infrastructure that can provide timely, accurate, and trusted information about ongoing activities in the network.
Optics-Enabled, In-Network Defense: DDoS attacks have increased in sophistication with advanced strategies to continuously adapt (e.g., changing threat postures dynamically) and induce collateral damage (i.e., higher latency and loss for legitimate traffic). Furthermore, advanced attacks may also employ reconnaissance (e.g., mapping the network to find bottleneck links) to target the network infrastructure itself. In light of these trends, state-of-art defenses (e.g., advanced scrubbing, emerging software-defined defenses, and programmable switching hardware) have fundamental shortcomings. This project will develop a new framework, referred to as Optics-enabled In-Network Defense for Extreme Terabit DDoS attacks.
Data-Driven Wireless Network Management: The transition to 5G and beyond is expected to witness not only an emergence of new applications such as mobile augmented and virtual reality, but also opens up the attack surface to both known, and previously unknown threats. Thus, wireless networks of the future will need better control and management at different temporal and traffic aggregation granularities (e.g., how to allocate spectrum, how to quarantine distributed attacks etc.). This project aims to develop scalable, machine learning based analytics on the data from a large set of geographically distributed wireless core network entities such as base stations.
Dr. Liu is a tenure-track Assistant Professor in the Department of Electrical and Computer Engineering at Boston University. His research interests are in systems and networking, and his group at BU is focusing on building next-generation networked systems. Prior to BU, Dr. Liu was a postdoctoral researcher at Carnegie Mellon University and obtained his PhD in Computer Science from Johns Hopkins University. His research papers have been published in top-tier venues such as SIGCOMM, NSDI, OSDI, and FAST. He is a recipient of the best paper award at USENIX FAST’19 for his work on large-scale distributed load balancing. His work received multiple recognitions, including ACM STOC “Best-of-Theory” plenary talk and USENIX ATC “Best-of-Rest”.