Mr Skumbuzo Zwane

Position : NGAP Lecturer
Telephone : 035 902 
Email : zwanesg@unizulu.ac.za
Office : 106, D-block Building, KwaDlangezwa Campus

Biography:

Skhumbuzo G. Zwane is currently a NGAP Lecturer, he holds a Master’s, Honours, and bachelor’s degree from the university of Zululand. During this period, he assisted junior students and conducted research in areas of cyber security, Software Defined Networking, Machine Learning and Natural Language Processing, which resulted in several peer reviewed publications in IEEE and SATNAC. Skhumbuzo have also participated in Data Science programs facilitated by CSIR, then ventured to industry where he worked as a consultant at Oracle Corporation South Africa, where he assisted with the deployment and adoption of various Oracle Fusion Applications, which include ERP, EPM, SCM, and HCM. Before his current position he worked as an Automation Testing engineer at MTN, developing automated testing suites for different applications across Oracle Cloud applications for several OpCo’s, including MTN Nigeria, Uganda, Cameroon, Fintech, and MTN South Africa. During this time, he collaborated and worked closely with different teams from Egypt, India, Nigeria, Netherlands, and South Africa.

 Lecture ‘s  the following modules:

  • 4CPS332 – Client Server Computing
  • 4CPS506 – Software Defined Networking Theory (Honours)

Qualifications:

MSc, Hons (Computer Science), BSc (Computer Science & Mathematics) (UNIZULU)

Research interests: 

Mobile Ad-Hoc Networks (MANETs), Software Defined Networks (SDN), Computer Network Security, Cyber Security, Intrusion Detection, Machine Learning and Neural Networks (ML & NN), Artificial Intelligence (AI), Natural Language Processing (NLP), Neural Machine Translation (NMT), Internet of Things (IoT)

  Publications 
  • Zwane, P. Tarwireyi and M. Adigun, “Performance Analysis of Machine Learning Classifiers for Intrusion Detection,” 2018 International Conference on Intelligent and Innovative Computing Applications (ICONIC), Mon Tresor, Mauritius, 2018, pp. 1-5, doi: 10.1109/ICONIC.2018.8601203.
  • Zwane, P. Tarwireyi and M. Adigun, “A Flow-based IDS for SDN-enabled Tactical Networks,” 2019 International Multidisciplinary Information Technology and Engineering Conference (IMITEC), Vanderbijlpark, South Africa, 2019, pp. 1-6, doi: 10.1109/IMITEC45504.2019.9015900.
  • J. Sefara, S. G. Zwane, N. Gama, H. Sibisi, P. N. Senoamadi and V. Marivate, “Transformer-based Machine Translation for Low-resourced Languages embedded with Language Identification,” 2021 Conference on Information Communications Technology and Society (ICTAS), Durban, South Africa, 2021, pp. 127-132, doi: 10.1109/ICTAS50802.2021.9394996.
  • Zwane, P. Tarwireyi and M. Adigun, “Ensemble Learning Approach for Flow-based Intrusion Detection System,” 2019 IEEE AFRICON, Accra, Ghana, 2019, pp. 1-8, doi: 10.1109/AFRICON46755.2019.9133979.
  • Skhumbuzo Zwane, Paul Tarwireyi, Matthew Adigun, “Ensemble Learning for Flow Based Intrusion Detection: A SDN implementation”, Southern Africa Telecommunication Networks and Applications Conference (SATNAC), Fairmont Zimbali Resort, Ballito, KwaZulu-Natal, South Africa 2019, pp. 288-298
  • Skhumbuzo Goodwill Zwane, Paul Tarwireyi, Ijeoma Mba, Matthew Adigun “High Performance Security Mechanism for Real-time Multimedia Sessions,” Southern Africa Telecommunication Networks and Applications Conference (SATNAC), Freedom of the Seas, Royal Caribbean International, Barcelona, Spain 2017, pp. 242-247