Ransomware Detection: Techniques, Challenges, and Future Directions
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Abstract
The ongoing development of ransomware threats calls for sophisticated detection methods that can lessen these widespread and damaging assaults. This survey report offers a thorough analysis of current ransomware detection methods, assesses their efficacy, points out problems, and considers potential directions for future investigation. We address the use of hybrid strategies, anomaly detection system integration, and machine learning algorithms in thwarting ransomware attacks by examining more than forty cutting-edge academic publications. Our goal is to offer a thorough resource that will direct future advancements in cybersecurity defenses against ransomware.
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