3 citations · 5 across the 5 of their papers we have counts for
6 papers
Red-MIRROR: Agentic LLM-based Autonomous Penetration Testing with Reflective Verification and Knowledge-augmented Interaction
Tran Vy Khang, Nguyen Dang Nguyen Khang, Nghi Hoang Khoa +3
Web applications remain the dominant attack surface in cybersecurity, where vulnerabilities such as SQL injection, XSS, and business logic flaws continue to cause significant data…
PenTiDef: Decentralized Federated Intrusion Detection System with Differential Privacy and Latent-Space Defense via Blockchain Coordination in IIoT
Phan The Duy, Nghi Hoang Khoa, Nguyen Tran Anh Quan +3
This paper proposes PenTiDef, a fully decentralized, privacy-preserving, and poisoning-resilient framework for decentralized federated IDS (DFL-IDS). PenTiDef synergistically integ…
DMLDroid: Deep Multimodal Fusion Framework for Android Malware Detection with Resilience to Code Obfuscation and Adversarial Perturbations
Doan Minh Trung, Tien Duc Anh Hao, Luong Hoang Minh +4
In recent years, learning-based Android malware detection has seen significant advancements, with detectors generally falling into three categories: string-based, image-based, and…
On the Effectiveness of Adversarial Samples against Ensemble Learning-based Windows PE Malware Detectors
Trong-Nghia To, Danh Le Kim, Do Thi Thu Hien +4
Recently, there has been a growing focus and interest in applying machine learning (ML) to the field of cybersecurity, particularly in malware detection and prevention. Several res…
XFedHunter: An Explainable Federated Learning Framework for Advanced Persistent Threat Detection in SDN
Huynh Thai Thi, Ngo Duc Hoang Son, Phan The Duy +3
Advanced Persistent Threat (APT) attacks are highly sophisticated and employ a multitude of advanced methods and techniques to target organizations and steal sensitive and confiden…
VulnSense: Efficient Vulnerability Detection in Ethereum Smart Contracts by Multimodal Learning with Graph Neural Network and Language Model
Phan The Duy, Nghi Hoang Khoa, Nguyen Huu Quyen +4
This paper presents VulnSense framework, a comprehensive approach to efficiently detect vulnerabilities in Ethereum smart contracts using a multimodal learning approach on graph-ba…