Xuan-Ha Nguyen

Highly accomplished AI Researcher with a proven track record of developing and applying innovative machine learning solutions to critical network security challenges. Demonstrated research excellence through 16+ peer-reviewed publications, including multiple ISI-Q1 journal articles, and a strong background as a Valedictorian and Top 1% graduate. Expertise spans advanced AI/ML algorithm development, intrusion detection systems, and robust programming skills, consistently driving impactful research outcomes.

• 2022/2023 | VINIF Scholarship for Domestic Masters and Doctoral Training 2022 and 2023
  Awarded by: Vingroup Innovation Foundation (VINIF)
  A prestigious scholarship supporting promising researchers in Vietnam. Limited to 250 scholarships per year.
  Only 2-3 talent researchers pass this scholarship within UIT per year
• 2022 | Certificate of Merit for Outstanding Graduates (2018-2022)
  Awarded by: Vietnam National University, Ho Chi Minh City (VNU-HCM) for students with consistent academic excellence throughout the undergraduate program.
• 2021 | Vietnamese Research Competition - Eureka
  Awarded by: Ho Chi Minh City Youth Union & Organisers of the Eureka Competition
  Achieved one project in the Final Round Participant (Top 10% of over 1500 attended projects)
  Achieved one project in: Semi-Final Round Participant
  A national-level competition fostering student scientific research.
• 2020 | Consolation Prize, ASEAN Student Contest on Information Security (Southern Region)
  Awarded by: Vietnam Information Security Association (VNISA)
  Recognising performance in a regional cybersecurity competition.
• 2019 | International Collegiate Programming Contest (ICPC) Achievements
  Organised by: ICPC Foundation; Vietnam Association for Information Processing
  Second Prize, Vietnam National Contest
  Honorable Mention, Asia Pacific Danang Regional Contest
• 2018 | Gold Medal, UITACM X Programming Competition
  Awarded by: University of Information Technology - Vietnam National University Ho Chi Minh City (UIT, VNU-HCM)
  Top award in the university's competitive programming contest.
• 2018 | International Collegiate Programming Contest (ICPC) Achievements
  Organised by: ICPC Foundation; Vietnam Association for Information Processing
  Third Prize, Vietnam Southern Provincial Programming Contest
  Third Prize, Vietnam National Programming Contest
  Honorable Mention (Third Prize, Domestic Teams), Asia Southeast and Pacific Hanoi Regional Contest

• Google Scholar H-index: 4; Citations: 190
• SciVal-FWCI as first author: 3.99
• Nguyen, Xuan-Ha, and Kim-Hung Le. "nNFST: A single-model approach for multiclass novelty detection in network intrusion detection systems." Journal of Network and Computer Applications (2025): 104128 - ISI-Q1, Impact Factor: 7.7. DOI: https://doi.org/10.1016/j.jnca.2025.104128
• Huynh, Hoang-Hai, Nguyen, Xuan-Ha, Nguyen, Xuan-Duong, and Kim-Hung Le. "BigSIDS: An Efficient SDN-based Network Intrusion Detection System for Big Data Environments." Cluster Computing - ISI-Q1, Impact factor: 3.6. Accepted and planned for publication in June 2025.
• Luu, Gia-Huy, Minh-Khang Duong, Trong-Phuc Pham-Ngo, Thanh-Sang Ngo, Dat-Thinh Nguyen, Xuan-Ha Nguyen, and Kim-Hung Le. "XSShield: A novel dataset and lightweight hybrid deep learning model for XSS attack detection." Results in Engineering 24 (2024): 103363 - ISI-Q1, Impact Factor: 6.0. DOI: https://doi.org/10.1016/j.rineng.2024.103363
• Nguyen, Xuan-Ha, and Kim-Hung Le. "Robust detection of unknown DoS/DDoS attacks in IoT networks using a hybrid learning model." Internet of Things 23 (2023): 100851. - ISI-Q1, Impact Factor: 5.9. DOI: https://doi.org/10.1016/j.iot.2023.100851
• Nguyen, Xuan-Ha, Dat-Thinh Nguyen, and Kim-Hung Le. "Benchmarking svm variants for unsupervised intrusion detection system." 2023 RIVF International Conference on Computing and Communication Technologies (RIVF). IEEE, 2023. DOI: https://doi.org/10.1109/RIVF60135.2023.10471784
• Nguyen, Xuan-Ha, Xuan-Duong Nguyen, and Kim-Hung Le. "Preventing Adversarial Attacks Against Deep Learning-Based Intrusion Detection System." International Conference on Information Security Practice and Experience. Cham: Springer International Publishing, 2022 - Rank B CORE2021. DOI: https://doi.org/10.1007/978-3-031-21280-2_21
• Nguyen, Xuan-Ha, Xuan-Duong Nguyen, Hoang-Hai Huynh, and Kim-Hung Le. "Realguard: A lightweight network intrusion detection system for IoT gateways." Sensors 22, no. 2 (2022): 432 - ISI-Q2, Impact Factor: 3.576. DOI: https://doi.org/10.3390/s22020432
• Includes 10 Scopus-indexed conference papers co-authored through the mentorship of students with Dr. Kim-Hung Le (2022-Present)

Real-time Network Intrusion Detection System for Internet of Things
[ 04/2021 – 01/2022 ]

• Engineered a Network Intrusion Detection System (NIDS) employing deep learning methodologies to proactively identify and classify diverse cyber-attack types within IoT networks.
• Developed and optimized novel deep learning architectures specifically for effective and real-time detection of malicious activities targeting IoT devices.
• Key Outcome: This research culminated in a publication in an ISI-Q2-indexed journal, demonstrating its contribution to enhancing the security posture of IoT ecosystems.
  

Machine Learning-Based Intrusion Detection System for Software-Defined Networks in Big Data Contexts
[ 06/2021 – 01/2022 ]

• Developed a comprehensive simulation environment for Software-Defined Networks (SDN), incorporating a distributed system architecture for efficient big data processing.
• Designed and implemented a deep learning-based NIDS tailored for SDN environments, demonstrating robust performance in handling high-volume network traffic and complex attack patterns.
• Key Outcome: This project led to a significant publication in an ISI-Q1 indexed journal, advancing the field of network security with a scalable ML-driven intrusion detection solution for SDN architectures.
  

AI-Driven Anomaly Detection for Security Cameras (Internship Project, Becamex IDC Corp)
[ 02/2021 – 06/2021 ]

• As an AI Researcher Intern at Becamex IDC Corp, Ideveloped and implemented AI algorithms for real-time analysis of object behaviours from security camera feeds to detect anomalous activities.
• Successfully deployed the AI solution on resource-constrained embedded devices within Becamex IDC Corp's local surveillance camera infrastructure, validating its performance in a real-world security scenario.