Tram Truong-Huu (in Vietnamese: Trương Hữu Trầm)

AI for Cybersecurity and Networking

AI for Network Anomaly, Attack Detection, and Classification 

• Y. Hou, S. G. Teo, Z. Chen, M. Wu, C.-K. Kwoh, T. Truong-Huu, "Handling Labeled Data Insufficiency: Semi-supervised Learning with Self-Training Mixup Decision Tree for Classification of Network Attacking Traffic," IEEE Transactions on Dependable and Secure Computing, July 2022.

• P. Pratim Kundu, T. Truong-Huu, L. Chen, L. Zhou, and Sin G. Teo, "Detection and Classification of Botnet Traffic using Deep Learning with Model Explanation," IEEE Transactions on Dependable and Secure Computing, June 2022 [PDF ].

• T.-D. Pham, T.-L. Ho, T. Truong-Huu, T.-D. Cao, and H.-L. Truong, "MAppGraph: Mobile-App Classification on Encrypted Network Traffic using Deep Graph Convolution Neural Networks," In Proceedings of the Annual Computer Security Applications Conference (ACSAC’21), December 2021, Virtual Conference.

• J. Liao, Sin G. Teo, P. Pratim Kundu, T. Truong-Huu, "ENAD: An Ensemble Framework for Unsupervised Network Anomaly Detection," 2021 IEEE International Conference on Cyber Security and Resilience (IEEE CSR), July 2021, Virtual Conference.

• T. Truong-Huu, N. Dheenadhayalan, P. Pratim Kundu, V. Ramnath, J. Liao, Sin G. Teo, and S. Praveen Kadiyala, "An Empirical Study on Unsupervised Network Anomaly Detection using Generative Adversarial Networks," in Proc. 1st Security and Privacy on Artificial Intelligence Workshop (SPAI’20) - collocated with AsiaCCS 2020, Oct. 2020, Taipei, Taiwan.

• A. R. Narayanadoss, T. Truong-Huu, P. M. Mohan and M. Gurusamy, "Crossfire Attack Detection using Deep Learning in Software-Defined ITS Networks," in Proc. IEEE VTC2019-Spring, Kuala Lumpur, Malaysia, Apr. 2019.

AI for Malware Detection and Classification 

• D. Rabadi, J. Y. Loo, A. Narayanan, Y. Wang, S. G. Teo, T. Truong-Huu, "FETA: A Systematic and Efficient Approach for Feature Engineering on Anti-Static and Anti-Dynamic Malware Analysis," Journal of Information Security and Applications, 2025.

• Y. Hou, T. Truong-Huu, Z. Chen, C.-K. Kwoh, S. G. Teo, "PROTEUS: Domain Adaptation for Dynamic Features in AI-assisted Windows Malware Detection," In Proceedings of the 2023 IEEE ICDM Workshop on Machine Learning for Cybersecurity, Shanghai, China, December 2023. 

• L.-Q. Yau, Y.-T. Lam, A. Lokesh, P. Gupta, J. Lim, I. S. Singh, J.-Y. Loo, M.-V. Ngo, S.-G. Teo, T. Truong-Huu, "A Novel Feature Vector for AI-assisted Windows Malware Detection," In Proceedings of the 21st IEEE International Conference on Dependable, Autonomic & Secure Computing (DASC 2023), Abu Dhabi, Nov. 2023.

• M-. V. Ngo, T. Truong-Huu, D. Rabadi, J. Y. Loo, S.-G. Teo, "Fast and Efficient Malware Detection with Joint Static and Dynamic Features Through Transfer Learning," In Proceedings of the 21st International Conference on Applied Cryptography and Network Security (ACNS 2023), Kyoto, Japan, June 2023. 

• P. Pratim Kundu, L. Anatharaman, T. Truong-Huu, "An Empirical Evaluation of Automated Machine Learning Techniques for Malware Detection," in Proc. 7th ACM International Workshop on Security and Privacy Analytics (IWSPA 2021), co-located with ACM CODASPY 2021, April 2021, Virtual Event.

• S. Praveen Kadiyala, A. Kartheek, T. Truong-Huu, "Program Behavior Analysis and Clustering using Performance Counters," in Proc. 2020 DYnamic and Novel Advances in Machine Learning and Intelligent Cyber Security (DYNAMICS) Workshop - collocated with ACM ACSAC 2020, Austin, Texas, USA, Dec. 2020. [PDF]

• W. L. Tan, T. Truong-Huu, "Enhancing Robustness of Malware Detection using Synthetically-adversarial Samples," in Proc. IEEE Globecom 2020, Taipei, Taiwan, Dec. 2020.

AI for  Next-generation Networking

• B. Trinh-Nguyen, S. Berri, S. G. Teo, T. Truong-Huu, A. Chorti, "High-accuracy AoA-based Localization using Hierarchical ML Classifiers in Outdoor Environments," IEEE GLOBECOM 2025, Taiwan, Dec. 2025.

• A. Abrol, P. M. Mohan,  and T. Truong-Huu, "A Deep Reinforcement Learning Approach for Adaptive Traffic Routing in Next-gen Networks," in Proc. IEEE ICC 2024, Denver, USA, June 2024.

• S. M. Srinivasan, T. Truong-Huu, and M. Gurusamy, "Machine Learning-based Link Fault Identification and Localization in Complex Networks," IEEE Internet Things J., vol. 6, no. 4, pp. 6556-6566, Aug. 2019.

• T. Truong-Huu, P. Prathap, P. M. Mohan, and M. Gurusamy, "Fast and Adaptive Failure Recovery using Machine Learning in Software Defined Networks," in Proc. IEEE ICC 2019 - DDINS Workshop, Shanghai, China, May 2019.

• S. M. Srinivasan, T. Truong-Huu, and M. Gurusamy, “TE-based Machine Learning Techniques for Link Fault Localization in Complex Networks,” in IEEE 6th International Conference on Future Internet of Things and Cloud (FiCloud-2018), Barcelona, Spain, Aug. 2018.

Federated Learning and Distributed Machine Learning

• T.-D. Cao, H.-T. Nguyen, M.-T. Nguyen, T. Truong-Huu, H.-L. Truong. "EADRAN: An Edge Marketplace for Federated Learning," Future Generation Computer Systems, vol. 175, Feb. 2026.

• T.-D. Cao, N.-T. Vuong, T.-Q. Le, H.-V.-N. Dao, T. Truong-Huu, "Asyn2F: An Asynchronous Federated Learning Framework with Bidirectional Model Aggregation," IEEE Transactions on Emerging Topics in Computing, Sept. 2025.

• M.-T. Nguyen, H.-L. Truong, T. Truong-Huu, “Novel Contract-based Runtime Explainability Framework for End-to-End Ensemble Machine Learning Serving,” 3rd International Conference on AI Engineering – Software Engineering for AI, 2024.

• T.-D. Cao, H.-L. Truong, T. Truong-Huu, M.-T. Nguyen, "Enabling Awareness of Quality of Training and Costs in Federated Machine Learning Marketplaces," In Proceedings of 15th IEEE/ACM International Conference on Utility and Cloud Computing (UCC2022), Portland, Oregon, USA, December 2022.

• H.-L. Truong, T. Truong-Huu, T.-D. Cao, "Making Distributed Edge Machine Learning for Resource-Constrained Communities and Environments Smarter: Contexts and Challenges," Journal of Reliable Intelligent Environments, April 2022.

• T.-D. Cao, T. Truong-Huu, H. Tran, K. Tran, "A Federated Deep Learning Framework for Privacy Preservation and Communication Efficiency," Journal of Systems Architecture, vol. 124, March 2022.