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Công bố khoa học

Tra cứu các công bố khoa học theo năm, loại công trình, tác giả và từ khóa.

Phạm vi thống kê: Năm 2026
28 công bố được hiển thị

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2026
Tạp chí Quốc tế SCIE Q1

Navigating and orchestrating Web 3.0 innovation challenges: A theory of cross-chain ecosystem strategy

Tuan-Dung Tran, Phuong-Dai Bui, Van-Hau Pham

Journal of Engineering and Technology Management - Ngày xuất bản:
Ngày được chấp nhận: -

Web 3.0 technologies present fundamental challenges to established theories of platform strategy and organizational design, yet the organizational forms enabling decentralized innovation remain theoretically underexamined. This paper reconceptualizes cross-chain bridges, which enable value and message transfer across independent blockchain networks, not as…

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2026
Hội nghị Quốc tế Scopus Indexed

PRECISE: Precision-Driven Discovery of Token-centric MEV

Dinh Khang Nguyen, Huynh Nhu Nguyen Thi, Bich Nhu Hong, Quang Trung Do, Tuan-Dung Tran, Van-Hau Pham

The 9th International Conference on Multimedia Analysis and Pattern Recognition (MAPR2026) - Ngày hội nghị: -
Ngày được chấp nhận: -

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2026
Hội nghị Quốc tế Scopus Indexed

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

Huu Nhien Dinh, Chau The Vi, Thai Hung Van, Trong-Nghia To, Phan The Duy

The 9th International Conference on Multimedia Analysis and Pattern Recognition (MAPR 2026) IEEE Ngày hội nghị: -
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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 spanning…

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2026
Hội nghị Quốc tế Scopus Indexed

Graph-Driven LLM-Augmented Stateful API Fuzzing for OWASP API Top 10

Khanh-Khoa Ngo, Trieu Huynh Pham Long, Truong Nguyen Van, Thai Hung Van, Phan The Duy

The 9th International Conference on Multimedia Analysis and Pattern Recognition (MAPR 2026) IEEE Ngày hội nghị: -
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Security testing of REST APIs remains difficult because real-world OpenAPI specifications are often incomplete, many security flaws are inherently stateful, and prevailing stateful fuzzers still optimize primarily for structural exploration rather than OWASP-aligned risk categories. Based on this gap, this paper presents…

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2026
Hội nghị Quốc tế Scopus Indexed

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

Cao Phan Xuan Qui, Le Quoc Ngo, Phan The Duy, Van-Hau Pham

The 9th International Conference on Multimedia Analysis and Pattern Recognition (MAPR 2026) IEEE Ngày hội nghị: -
Ngày được chấp nhận: -

Network Intrusion Detection Systems (NIDS) based on machine learning must evolve after deployment to detect emerging threats very soon with a few labeled samples, while without catastrophic forgetting or degrading due to concept drift. Existing methods address these issues in isolation, lacking…

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2026
Tạp chí Quốc tế SCIE Q1

MORPH-IDS: A Context-Driven Multi-Agent Reinforcement Learning Framework for Drift-Aware Moving Target Defense in Adversarial-Robust Intrusion Detection

Truong Duc Hao, Hong Huy Hoang, Le Hong Hien, Dang Van Huynh, Quan Le-Trung, Van-Hau Pham, Phan The Duy

Computer Networks Elsevier Ngày xuất bản: -
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In the rapidly evolving cybersecurity landscape, Machine Learning (ML)-based Network Intrusion Detection Systems (NIDS) have become essential for detecting sophisticated threats, yet they are increasingly vulnerable to adversarial evasion attacks and concept drift caused by adaptive attackers. Existing ensemble-based defenses optimize for…

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2026
Tạp chí Quốc tế SCIE Q1

XDFC-IDS: An Explainable Decentralized Federated Class-Incremental Fusion Framework for Intrusion Detection

Nguyen Huu Quyen, Van-Hau Pham, Phan The Duy

Expert Systems with Applications Elsevier Ngày xuất bản: -
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With the widespread adoption of IoT and edge computing, federated learning (FL)-based intrusion detection systems (IDSs), which enable privacy-preserving, cost-effective training by fusing knowledge extracted from collaborators without centralizing the sensitive data, have become essential. Specifically, decentralized FL (DFL)-based IDSs are increasingly…

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2026
Tạp chí Quốc tế SCIE Q1

Poisoning the Swarm: Evaluating Data-Level Vulnerabilities in Decentralized Internet of Medical Things-enabled Healthcare Networks

Ngo Duc Hoang Son, Vuong Dinh Thanh Ngan, Le Minh Nha, Tran Duc Luong, Van-Hau Pham, Phan The Duy

Computers and Electrical Engineering Elsevier Ngày xuất bản: -
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Swarm Learning (SL) integrates federated learning and blockchain to support decentralized privacy-preserving learning for smart healthcare. However, the resilience of its learning and aggregation process against malicious data injection remains underexplored. This study presents a vulnerability analysis of SL against data-level poisoning,…

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2026
Tạp chí Quốc tế Q1

Enhanced android malware classification using multi machine learning models and generative adversarial network

Nguyen Tan Cam, Nguyen Cong Danh, Nghi Hoang Khoa

Neural Computing and Applications Springer Ngày xuất bản:
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Android malware is increasingly becoming a serious security threat to users as the popularity of mobile phones continues to rise. The application of machine learning models for classifying Android malware has been widely used in related studies. However, machine learning models can…

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2026
Tạp chí Quốc tế SCIE Q1

P4P: A Probe-Guided Anti-Poisoning Defense for Federated Learning-based Intrusion Detection in IoT Networks under Non-IID Data

Thai Tuan Khang, Tran Huu Duc, Dang Van Huynh, Van-Hau Pham, Phan The Duy

Journal of Network and Computer Applications - Ngày xuất bản: -
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Federated learning (FL) enables collaborative Intrusion Detection Systems (IDS) across distributed Internet of Things (IoT) networks without sharing raw data. However, its openness exposes it to model poisoning and backdoor attacks, where malicious clients manipulate updates to corrupt the global model. Detecting…

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2026
Tạp chí Quốc tế SCIE Q1

AutoWAFuzzer: An Adaptive Framework for Web Application Firewall Penetration Testing with Multi-agent System and RAG-enabled Reinforcement Learning

Phan The Duy, Nguyen Ngoc Thanh, Pham Cong Lap, Van-Giau Ung, Khanh-Khoa Ngo, Tram Truong-Huu, Van-Hau Pham

Expert Systems with Applications Elsevier Ngày xuất bản: -
Ngày được chấp nhận: -

Web Application Firewalls (WAFs) are crucial in mitigating web-based threats such as SQLi and XSS, yet the evolving complexity of WAF detection mechanisms poses significant challenges for penetration testing (pentest) tools. Existing ML- and RL-based fuzzers often suffer from three main limitations:…

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2026
Tạp chí Quốc tế SCIE Q1

A Multimodal Approach for Windows Malware Detection using Comprehensive Analysis on Called APIs

Do Thi Thu Hien, Bao Pham-Thai, Nguyen Tan Cam, Van-Hau Pham

Journal of Information Security and Applications Elsevier Ngày xuất bản:
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With the continuous evolution of the Windows operating system, malware-especially those based on Portable Executable (PE) files-has become increasingly sophisticated. Recent studies have widely adopted artificial intelligence (AI), particularly deep learning (DL) models, for malware detection. Among these, approaches focusing on API…

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2026
Tạp chí Quốc tế SCIE Q1

A study on functionality validation for windows malware mutating using reinforcement learning

Do Thi Thu Hien, Le Viet Tai Man, Le Trong Nhan, Phan Ngoc Yen Nhi, Hoang Thanh Lam, Nguyen Tan Cam, Van-Hau Pham

Information and Software Technology Elsevier Ngày xuất bản:
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To keep pace with the rapid advancements in both the quality and complexity of malware, recent research has extensively employed machine learning (ML) and deep learning (DL) models to detect malicious software, particularly in the widely used Windows system. Despite demonstrating promising…

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2026
Tạp chí Quốc tế SCIE Q1

xPriMES: Explainable Reinforcement Learning-guided Mutation Strategy with Dual-Environment Interaction for Evading Black-box Malware Detectors

Phan The Duy, Nguyen Manh Cuong, Ha Trieu Yen Vy, Le Tuan Luong, Nguyen Tran Duc Anh, Nghi Hoang Khoa, Van-Hau Pham

Information and Software Technology Elsevier Ngày xuất bản:
Ngày được chấp nhận: -

Malware continues to evolve, exposing weaknesses in conventional detectors and motivating realistic adversarial evaluations. Prior RL-based evasion methods often rely on partial model access or feature-level perturbations, limiting realism under strict black-box constraints. We propose xPriMES, a dual-environment reinforcement learning framework that…

Chi tiết Liên kết ngoài
2026
Tạp chí Quốc tế SCIE Q1

Android malware detection by using graph optimization of static features based on pre-trained language models

Nghi Hoang Khoa, Doan Minh Trung, Duong The Dat, Phan The Duy, Van-Hau Pham, Nguyen Tan Cam

Information and Software Technology Elsevier Ngày xuất bản:
Ngày được chấp nhận: -

The Android platform is the dominant mobile operating system, making it a prime target for malware attacks. The increasing complexity of Android malware necessitates advanced detection methods that integrate modern machine learning techniques with security analysis. This study aims to enhance Android…

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2026
Tạp chí Quốc tế SCIE Q1

Hawkeyes: An Intelligent Honeypot Allocation Strategy for Cyber Deception using Reinforcement Learning

Hien Do Hoang, Trong-Nghia To, Ngo Duc Hoang Son, Khoa Ngo-Khanh, Nguyen Tan Cam, Van-Hau Pham

Computer Networks Elsevier Ngày xuất bản:
Ngày được chấp nhận: -

Honeypot allocation has emerged as a pivotal strategy in cyber deception. However, existing approaches often face scalability issues, limited coordination, and inadequate consideration of intrusion stages, which constrain their effectiveness in complex attack environments. To address these challenges, this study introduces Hawkeyes,…

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