부산대학교 도서관

Ransomware attacks have emerged as a significant threat to organizations and individuals, causing substantial financial and operational damages worldwide. With the increasing sophistication and frequency of ransomware attacks, it is crucial to develop effective detection mechanisms to identify and mitigate these threats. Machine learning techniques have gained prominence in detecting ransomware attacks due to their ability to analyze large volumes of data and identify patterns indicative of malicious activities. This systematic review aims to provide a comprehensive analysis of the existing literature on ransomware attack detection using machine learning techniques.