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Author

Duy The Phan

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Conference Aug 2026

A Class-incremental and Few-shot learning model for Intrusion detection under Concept drift

Network Intrusion Detection Systems (NIDS) based on machine learning must evolve after deployment to promptly detect emerging threats from only a few labeled samples, without catastrophically forgetting known attacks or degrading under concept drift. Existing methods address these issues in isolation, lacking a unified...

Cao Phan Xuan Qui, Le Quoc Ngo, Duy The Phan et al. · 0 citations
Conference Aug 2026

S-AECR: Word Intelligence and Explanation Strategy for Cyber Threat Intelligence Extraction and Mapping

Cyber Threat Intelligence (CTI) reports are the primary source of actionable threat knowledge; however, most high-value content is published in unstructured text, creating a significant bottleneck for operational threat response. Manual extraction of Indicators of Compromise (IoC), cybersecurity entities, and Tactics,...

An Bao Tran, Kiệt Nguyễn Văn, Duy The Phan · 0 citations
Aug 2026

Evaluating the Robustness and Transferable Adversarial Example Resistance of Multimodal Learning-based Intrusion Detection Systems against Evasion Attacks

This study evaluates the robustness of multimodal learning-based IDS against transferable adversarial examples (AEs) generated by Generative Adversarial Networks (GANs) and integrates adversarial training techniques to enhance the IDS’s capability to identify attack patterns with small perturbations.

Duy The Phan, Cao The Thuan, Q. Doan et al. · 0 citations
Conference Aug 2026

An Empirical Study on the Transferability of Transformer-Based Models for Software Vulnerability Detection

Despite the dominance of Transformer-based models in software vulnerability detection, the extent to which their learned security logic generalizes across different programming languages remains a critical open question. To address this, we propose a comprehensive evaluation framework organized into three phases spanni...

Nhien Huu Dinh, Chau The, Thai Hung Van et al. · 0 citations
Conference Jul 2026

Active Digital Twin Verification for Robust Federated Learning in IoT Intrusion Detection

Federated Learning has become a practical approach for training intrusion detection models across distributed Internet of Things devices, but it remains exposed to poisoning attacks, non-IID data heterogeneity, and free-rider exploitation. This paper presents DT-Guard, a defense framework that leverages a server-side D...

H. Pham, Duy The Phan, Van-Hau Pham · 0 citations

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