An optimized hybrid ensemble machine learning model combining multiple classifiers for detecting advanced persistent threats in networks

Journal of Big Data  (ISSN: 2196-1115 )
DOI: https://doi.org/10.1186/s40537-025-01272-w

A Novel Machine Learning Model for Early Detection of Advanced Persistent Threats Utilizing Semi-Synthetic Network Traffic Data

Journal of VLSI Circuits and Systems (ISSN 2582-1458)
DOI: https://doi.org/10.31838/jvcs/06.02.04 

Exploration of Defensive Strategies, Detection Mechanisms, and Response Tactics against Advanced Persistent Threats APTs

Nanotechnology Perceptions (ISSN 1660-6795)
DOI: https://doi.org/10.62441/nano-ntp.v20iS4.33 

Enhancing Cybersecurity in Software-Defined Networking: A Hybrid Approach for Advanced DDoS Detection and Mitigation

Nanotechnology Perceptions (ISSN 1660-6795)
DOI: https://doi.org/10.62441/nano-ntp.v20iS4.39

Cyber Resilience to Digital Threats for Education Institutions 4.0

International Journal of Management Science and Application (IJMSA), Sultan Publishers (ISSN 2963-2056 )
DOI: https://doi.org/10.58291/ijmsa.v4i1.370 

A Detection Of Advanced Persistent Threats Using Ensemble Based Machine Learning Approaches

PhD thesis on Shodhganga