23 citations · 23 across the 9 of their papers we have counts for
4 papers · 1 filter
DeepFaith: Evidence-Grounded LLMs for Faithful Incident Reporting in Multi-Stage APT Defense
Trung V. Phan, Tri Gia Nguyen, Thomas Bauschert
Advanced Persistent Threats (APTs) are difficult to detect and interpret due to their multi-stage and stealthy nature. While recent autonomous defense systems leverage provenance g…
DeepXplain: XAI-Guided Autonomous Defense Against Multi-Stage APT Campaigns
Trung V. Phan, Thomas Bauschert
Advanced Persistent Threats (APTs) are stealthy, multi-stage attacks that require adaptive and timely defense. While deep reinforcement learning (DRL) enables autonomous cyber defe…
DeepStage: Learning Autonomous Defense Policies Against Multi-Stage APT Campaigns
Trung V. Phan, Tri Gia Nguyen, Thomas Bauschert
This paper presents DeepStage, a deep reinforcement learning (DRL) framework for adaptive and stage-aware defense against Advanced Persistent Threats (APTs). The enterprise environ…
Learning the APT Kill Chain: Temporal Reasoning over Provenance Data for Attack Stage Estimation
Trung V. Phan, Thomas Bauschert
Advanced Persistent Threats (APTs) evolve through multiple stages, each exhibiting distinct temporal and structural behaviors. Accurate stage estimation is critical for enabling ad…