Dr. Ghulam Mohi-ud-din

       Computer Teacher

       School of Software, Nanchang University

         Email:mohiuddin@ncu.edu.cn

Overview:

Dr. Mohi-ud-din holds a position of Computer Teacher at the School of Software, Nanchang University.

He obtained his master’s and Ph.D. degrees from the University of Florida, USA, and holds a Ph.D. from Northwestern Polytechnical University, Xi’an, P.R. China.He has worked as a foreign expert at the University of Florida, USA, and Northwestern Polytechnical University, Xi’an, P.R. China. He also served as a Computer Science Lecturer at Nanchang Hangkong University, Nanchang P.R. China. From the research and Development perspective, he has worked at Google Inc., IBM, Oracle Inc., and Cisco Inc.

Over time,  Dr. Mohi-ud-din holds several certifications, including Cisco Certified Internetwork Expert (CCIE), Oracle Certified Expert (OCE), Project Management Professional (PMP), Sun Certified Java Expert (SCJE), etc.

Dr. Mohi-ud-din is a member of several international organizations, including ACM, IEEE BRCS, etc.

Research Area: Artificial Intelligence, Space Security, Critical Infrastructure Protection, Software Engineering, and Software Project Management

Funding：

1.20000 £, R&D Funding, Zero Day attack in Intrusion Detection System, ResearchEx Ltd, UK, (2020)

Publications:

1. Deciphering TON-IoT Threats: Meta-heuristic and Deep Learning for Attack Classification, Expert Systems with Applications, 2024

2. Joint High-resolution feature learning and vessel-shape aware convolutions for efficient vessel segmentation, Computers in Biology, 2024

3. Enabling Peephole and Meta-Heuristic Approaches for Coal Energy Consumption Rate Prediction, Computer and Electrical Engineering, 2024

4. ML-Driven Audit Risk Assessment with Differential Privacy, ISCMI, Melbourne, Australia, 2024

5. Optimizing Machine Learning Models: A Comprehensive Study on Integration Strategies and Their Impact on Performance, ICCOMIT, Edinburgh, UK, 2024

6. Intrusion Detection using hybridized Meta-heuristic techniques with Weighted XGBoost Classifier, Expert Systems with Applications, 2023-12.

7. Intrusion Detection Using Hybrid Enhanced CSA-PSO and Multivariate WLS Random-forest technique, IEEE Transactions on Network and Service Management,

8. Intrusion detection in wireless sensor network using enhanced empirical based component analysis, Future Generation Computer Systems, 2022-10.

9. NIDS: Random Forest Based Novel Network Intrusion Detection System for Enhanced Cybersecurity in VANET's, 2022 International Conference on Virtual Reality, Human-Computer Interaction and Artificial Intelligence (VRHCIAI), 2022-10.

10. A novel deep learning based security assessment framework for enhanced security in swarm network environment, International Journal of Critical Infrastructure Protection, 2022-09.

11. Modeling Network Intrusion Detection System Using Feed-Forward Neural Network Using UNSW-NB15 Dataset, 2019 IEEE 7th International Conference on Smart Energy Grid Engineering (SEGE), 2019-08.

12. Cross Regional Cluster of Message-Oriented Middleware, 2017 International Conference on Computer Systems, Electronics and Control (ICCSEC), 2017-12.

13. Secure addressing mechanism in MIPv6 by routing-header verification, 2017 IEEE 17th International Conference on Communication Technology (ICCT), 2017-10.

14. A Three-Layer Architecture for Intelligent Intrusion Detection Using Deep Learning, Advances in Intelligent Systems and Computing, 2019.

15.Deep Learning Approach for IDS Using DNN for Network Anomaly Detection, Advances in Intelligent Systems and Computing, 2018.

Books:

1.Key Issues in Network Protocols and Security, 2024