Dynamic Threat Mitigation: Harnessing Machine Learning for Behavior-Centric Malware Detection

EasyChair Preprint 12036

Abstract

With the relentless evolution of malware, traditional signature-based detection methods prove insufficient in safeguarding systems against dynamic threats. This paper introduces a novel approach to malware detection, leveraging machine learning for dynamic threat analysis. Our focus is on behavior-centric detection, where the system learns and adapts to the evolving tactics of malicious entities. By analyzing real-time behavior patterns, our model identifies and mitigates threats proactively, providing a robust defense mechanism against the ever-changing landscape of cyber threats.

Keyphrases: Behavior-centric, Cybersecurity, Dynamic Threat Analysis, Proactive Defense, Threat Mitigation, machine learning, malware detection

@booklet{EasyChair:12036,
  author    = {Battle Hurry},
  title     = {Dynamic Threat Mitigation: Harnessing Machine Learning for Behavior-Centric Malware Detection},
  howpublished = {EasyChair Preprint 12036},
  year      = {EasyChair, 2024}}