KEYNOTE Speakers

 

Prof. Minghua Chen (ACM Distinguished Scientist, Fellow of the IEEE, Fellow of the Asia-Pacific Artificial Intelligence Association)
City University of Hong Kong, China

Biography: Prof. Chen received his B.Eng. and M.S. degrees from the Department of Electronic Engineering at Tsinghua University. He received his Ph.D. degree from the Department of Electrical Engineering and Computer Sciences at University of California Berkeley. He was with Microsoft Research Redmond and Department of Information Engineering, the Chinese University of Hong Kong, before joining the School of Data Science, City University of Hong Kong.

Prof. Chen received the Eli Jury award from UC Berkeley in 2007 (presented to a graduate student or recent alumnus for outstanding achievement in the area of Systems, Communications, Control, or Signal Processing) and The Chinese University of Hong Kong Young Researcher Award in 2013. He also received several best paper awards, including IEEE ICME Best Paper Award in 2009, IEEE Transactions on Multimedia Prize Paper Award in 2009, ACM Multimedia Best Paper Award in 2012, IEEE INFOCOM Best Poster Award in 2021, and ACM e-Energy Best Paper Award in 2023. He also co-authors several papers that are Best Paper Award Runner-up/Finalist/Candidate of flagship conferences including ACM MobiHoc in 2014 and ACM e-Energy in 2015, 2016, 2018, and 2019. Prof. Chen serves as TPC Co-Chair, General Chair, and Steering Committee Chair of ACM e-Energy in 2016, 2017, and 2018 - 2021, respectively. He also serves as Associate Editor of IEEE/ACM Transactions on Networking in 2014 - 2018. He receives the ACM Recognition of Service Award in 2017 for the service contribution to the research community. He is currently a Senior Editor for IEEE Systems Journal (2021- present), an Area Editor of ACM SIGEnergy Energy Informatics Review (2021 - present), and an Executive Committee member of ACM SIGEnergy (2018 - present). He is an ACM Distinguished Member and an IEEE Fellow.

Prof. Chen's recent research interests include online optimization and algorithms, machine learning in power system operations, intelligent transportation systems, distributed optimization, delay-constrained network coding, and capitalizing the benefit of data-driven prediction in algorithm/system design.

 

Prof. Ljiljana Trajkovic (Fellow of IEEE)
Simon Fraser University, Canada

Speech Title: Machine Learning for Detecting Internet Traffic Anomalies

Abstract: Collection and analysis of data from deployed networks is essential for understanding communication networks. Hence, data mining and statistical analysis of network data have been employed to determine traffic loads, analyze patterns of users' behavior, predict future network traffic, and detect traffic anomalies. The Internet has historically been prone to failures and attacks that significantly degrade its performance, affect the Internet connectivity, and cause routing disconnections. Frequent cases of various cyber threats have been encountered over the years and, hence, detection of anomalous behavior is a topic of great interest in cybersecurity. In described case studies, traffic traces collected by various collection sites are used to classify network anomalies. Various anomaly and intrusion detection approaches based on machine learning have been employed to analyze collected data. Deep learning, broad learning, gradient boosted decision trees, and reservoir computing algorithms were used to develop models based on collected datasets that contain Internet worms, viruses, power outages, ransomware events, router misconfigurations, Internet Protocol hijacks, and infrastructure failures in times of conflict. The reported results indicate that while performance of machine learning models greatly depends on the used datasets, they are viable tools for detecting the Internet anomalies.

Biography: Ljiljana Trajkovic received the Dipl. Ing. degree from University of Pristina, Yugoslavia, the M.Sc. degrees in electrical engineering and computer engineering from Syracuse University, Syracuse, NY, and the Ph.D. degree in electrical engineering from University of California at Los Angeles. She is currently a professor in the School of Engineering Science, Simon Fraser University, Burnaby, British Columbia, Canada. Her research interests include communication networks and dynamical systems. Dr. Trajkovic served as IEEE Division X Delegate/Director, President of the IEEE Systems, Man, and Cybernetics Society, and President of the IEEE Circuits and Systems Society. She serves as Editor-in-Chief of the IEEE Transactions on Human-Machine Systems. She was a Distinguished Lecturer of the IEEE Circuits and System Society and a Distinguished Lecturer of the IEEE Systems, Man, and Cybernetics Society. She is a Fellow of the IEEE.