Zhida Li received the B.E. and M.A.Sc. degrees in Electrical Engineering and Microelectronic Design from the University College Cork, Ireland, in 2011 and 2015, respectively. He was a research assistant at Tyndall National Institute, Cork, Ireland, from 2011 to 2014. He is currently working toward the Ph.D. degree in Simon Fraser University from Fall 2015. His current research project is related to machine learning techniques for classifying network anomalies and intrusions.
He serves as Vice Chair (2020-2021) and served as Secretary (2019-2020) of the IEEE SFU Student Branch.
Zhida Li was the TA for ENSC 252 (Fundamentals of Digital Logic and Design) in Fall 2015 and Summer 2016,
ENSC 180 (Introduction to Engineering Analysis) in Spring 2017, ENSC 220 (Electric Circuit I) in Fall 2016,
Fall 2017, Summer 2018, Summer 2020, and ENSC 427/835 (Communication Networks) in Spring 2018-2020.
He is the IEEE graduate student member.
Supervisor: Prof. Ljiljana Trajkovic
- Machine Learning System for Classifying Anomalies and Intrusions in Communication Networks
- Focus on the development of a new machine learning algorithm.
- Implement and compare various machine learning algorithms (SVM, LSTM, GRU, BLS) for detecting network anomalies.
- Execute extensive amount of experiments on super computer and analyze the experiment results.
- BGP Anomaly Detection Tool
- Build an integrated/automatic tool that consists of 8 modules: real time data retrieving, feature extraction, data partition, data processing, ML algorithms, parameter selection, ML models, and classification.
Z. Li, A. L. Gonzalez Rios, and Lj. Trajkovic,
Machine learning for detecting anomalies and intrusions in communication networks,"
in IEEE Journal on Selected Areas in Communications (J-SAC), accepted.
Z. Li, A. L. Gonzalez Rios, and Lj. Trajkovic,
"Detecting Internet worms, ransomware, and blackouts using recurrent neural networks,"
in Proc. IEEE International Conference on Systems, Man, and Cybernetics,
Toronto, Canada, Oct. 2020, pp. 2165-2172.
A. L. Gonzalez Rios, Z. Li, K. Bekshentayeva, and Lj. Trajkovic,
"Detection of denial of service attacks in communication networks,"
IEEE Int. Symp. Circuits and Systems, Seville, Spain, Oct. 2020.
Z. Li, A. L. Gonzalez Rios, G. Xu, and Lj. Trajkovic,
"Machine learning techniques for classifying network anomalies and intrusions,"
in Proc. IEEE Int. Symp. Circuits and Systems, Sapporo, Japan, May 2019, pp. 1-4.
A. L. Gonzalez Rios, Z. Li, G. Xu, A. Diaz Alonso, and Lj. Trajkovic,
"Detecting network anomalies and intrusions in communication networks,"
in Proc. 23rd IEEE Int. Conference on Intelligent Engineering Systems 2019,
Godollo, Hungary, April 2019, pp. 29-34.
Z. Li, P. Batta, and Lj. Trajkovic,
of machine learning algorithms for detection of network intrusions,"
IEEE Int. Conference on Systems, Man, and Cybernetics (SMC 2018),
Miyazaki, Japan, Oct. 2018, pp. 4238-4243.
Q. Ding, Z. Li, S. Haeri, and Lj. Trajkovic,
of machine learning techniques to detecting anomalies in communication networks: datasets and feature selection algorithms,"
in Cyber Threat Intelligence, M. Conti, A. Dehghantanha, and T. Dargahi, Eds., Berlin: Springer, pp. 47-70, 2018.
Z. Li, Q. Ding, S. Haeri, and Lj. Trajkovic,
of machine learning techniques to detecting anomalies in communication networks: classification algorithms,"
in Cyber Threat Intelligence, M. Conti, A. Dehghantanha, and T. Dargahi, Eds., Berlin: Springer, pp. 71-92, 2018.
P. Batta, M. Singh, Z. Li, Q. Ding, and Lj. Trajkovic,
"Evaluation of support vector machine kernels for detecting network anomalies,"
IEEE Int. Symp. Circuits and Systems, Florence, Italy, May 2018, pp. 1-4.
H. Ben Yedder, Q. Ding, U. Zakia, Z. Li, S. Haeri, and Lj. Trajkovic,
virtualization algorithms and topologies for data center networks,"
The 26th Int. Conference on Computer Communications and Networks (ICCCN 2017),
2nd Workshop on Network Security Analytics and Automation (NSAA),
Vancouver, Canada, Aug. 2017.
Q. Ding, Z. Li, P. Batta, and Lj. Trajkovic,
"Detecting BGP anomalies using machine learning techniques,"
in Proc. IEEE Int. Conference on Systems, Man, and Cybernetics (SMC 2016),
Budapest, Hungary, Oct. 2016, pp. 3352-3355.
S. Haeri, Q. Ding, Z. Li, and Lj. Trajkovic,
resource capacity algorithm with path splitting for virtual network embedding,"
in Proc. IEEE Int. Symp. Circuits and Systems,
Montreal, Canada, May 2016, pp. 666-669.
M.P. Kennedy, H. Mo, Z. Li, G. Hu, P. Scognamiglio, and E. Napoli,
The Noise and Spur Delusion in Fractional-N Frequency Synthesizer Design,"
The IEEE Int. Symposium on Circuits and Systems (ISCAS),
Lisbon, Portugal, 24-27 May 2015.
Z. Li, H. Mo, and M.P. Kennedy,
Comparative Spur Performance of a Fractional-N Frequency Synthesizer
with a Nested MASH-SQ3 Divider Controller in the Presence of Memoryless Piecewise-Linear and Polynomial Nonlinearities,"
in Proc. ISSC 2014,
Limerick, 26-27 June 2014, pp. 1-6.
M.P. Kennedy, Z. Li, and H. Mo,
"How to Eliminate Integer Boundary Spurs in Fractional-N Frequency Synthesizers?,"
in Proc. Communication and Radio Sciences into the 21st Century,
Dublin, 30 April-01 May 2014, pp. 1-4.
M.P. Kennedy, Z. Li, and Z. Huang,
Programmable analog frequency divider based on p-switching,"
Nonlinear Theory and Its Applications, IEICE,
4(4): 389-399, 01 October 2013.
Z. Li and M.P. Kennedy,
"The Switched Injection-Locked Oscillator (SILO) Concept,"
in Proc. Nonlinear Theory and Its Applications (NOLTA) 2012,
Palma, Mallorca, 22-26 October 2012, pp. 868-871.
Detection of network anomalies