The Role of Behavioral Analysis in Ransomware Detection and Prevention

EasyChair Preprint 14925

Abstract

The escalating threat of ransomware attacks underscores the urgent need for effective detection and prevention strategies. Traditional security measures, while valuable, often fall short in identifying and mitigating sophisticated ransomware threats. This paper explores the integration of behavioral analysis into ransomware defense mechanisms, proposing a paradigm shift from signature-based to behavior-based detection approaches. By analyzing patterns of user and system behavior, behavioral analysis can provide deeper insights into the subtle indicators of ransomware activity. This study examines various behavioral analysis techniques, including anomaly detection, machine learning algorithms, and heuristics, and their efficacy in identifying early signs of ransomware. It also addresses the challenges associated with behavioral analysis, such as high false positive rates and the need for continuous adaptation to evolving threats. Through a review of current methodologies and case studies, this paper highlights the potential of behavioral analysis to enhance ransomware detection and prevention, offering a more dynamic and resilient approach to cybersecurity.

Keyphrases: Inadvertent Mistakes, malicious activities, psychological factors

@booklet{EasyChair:14925,
  author    = {Adeyeye Barnabas},
  title     = {The Role of Behavioral Analysis in Ransomware Detection and Prevention},
  howpublished = {EasyChair Preprint 14925},
  year      = {EasyChair, 2024}}