3 papers
cs.CR2026
TL-RL-FusionNet: An Adaptive and Efficient Reinforcement Learning-Driven Transfer Learning Framework for Detecting Evolving Ransomware Threats
Jannatul Ferdous, Rafiqul Islam, Arash Mahboubi +1
Modern ransomware exhibits polymorphic and evasive behaviors by frequently modifying execution patterns to evade detection. This dynamic nature disrupts feature spaces and limits t…
cs.CR2025
A Sysmon Incremental Learning System for Ransomware Analysis and Detection
Jamil Ispahany, MD Rafiqul Islam, M. Arif Khan +1
In the face of increasing cyber threats, particularly ransomware attacks, there is a pressing need for advanced detection and analysis systems that adapt to evolving malware behavi…
cs.CR2025
iCNN-LSTM: A batch-based incremental ransomware detection system using Sysmon
Jamil Ispahany, MD Rafiqul Islam, M. Arif Khan +1
In response to the increasing ransomware threat, this study presents a novel detection system that integrates Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM)…