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

EasyChair Preprint no. 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, machine learning, malware detection, Proactive Defense, Threat Mitigation

@Booklet{EasyChair:12036,
  author = {Battle Hurry},
  title = {Dynamic Threat Mitigation: Harnessing Machine Learning for Behavior-Centric Malware Detection},
  howpublished = {EasyChair Preprint no. 12036},

  year = {EasyChair, 2024}}