Keynote Speakers

Professor,  Ljiljana Trajkovic, Simon Fraser University, Canada（IEEE Fellow）

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 is and a Distinguished Lecturer of the IEEE Systems, Man, and Cybernetics Society a was a Distinguished Lecturer of the IEEE Circuits and System Society. She is a Fellow of the IEEE.

Speech Title: Data Mining and Machine Learning for Analysis of Network Traffic

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.

Professor, Jiliang Zhang, Northeastern University, China

Biography:  Jiliang Zhang is currently a full Professor at College of Information Science and Engineering, Northeastern University, Shenyang, China. He received the B.E., M.E., and Ph.D. degrees from the Harbin Institute of Technology, Harbin, China, in 2007, 2009, and 2014, respectively. He was an Associate Professor with the School of Information Science and Engineering, Lanzhou University from 2017 to 2019, and a researcher at the Department of Electrical Engineering, Chalmers University of Technology, Gothenburg, Sweden from 2017 to 2018, a Marie Curie Research Fellow and a KTP associate at the Department of Electronic and Electrical Engineering, The University of Sheffield, Sheffield, UK from 2018 to 2022. His research interests include, but are not limited to wireless channel modeling, modulation system, relay system, vehicular communications, ultra-dense small cell networks, and smart environment modeling. He has pioneered systematic building wireless performance evaluation, modeling, and optimization, with the key concepts summarized in Fundamental Wireless Performance of a Building, IEEE Wireless Communications, 29(1), 2022. He is also the Academic Editor for Wireless Communications and Mobile Computing since 2019. He was the recipient of the IEEE Wireless Communications Letters Exemplary Reviewer Award in both 2021 and 2022.

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Professor, Reggie Davidrajuh, University of Stavanger Stavanger, Norway 

Biography: Dr. Reggie Davidrajuh has a Master's degree in Control Systems and a Ph.D. in Industrial Engineering, both awarded by the Norwegian University of Science and Technology, Norway. He also has a D.Sc. (habilitation) degree in Information Science (awarded by the AGH University of Science and Technology, Poland) and one more Ph.D. in Mechanical Engineering (Silesian University of Technology, Poland).  He is presently a professor of Informatics at the University of Stavanger, Norway, and holds a visiting professor position at the Silesian University of Technology, Poland. He is an elected member of the Norwegian Academy of Technical Sciences. He is also a Senior Member of IEEE (SMIEEE), a Fellow of the British Computer Society (FBCS), and a Fellow of the International Artificial Intelligence Industry Alliance (FAIIA). His current research interests are "Modeling, simulation, and performance analysis of discrete-event systems" and Algorithms.

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