Ransomware Detection techniques in the Dawn of Artificial Intelligence: A Survey

Abstract

Ransomware is a class of malware that gains unauthorized admittance to organizational and personal assets and blocks their access to legitimate users and staff. It accomplishes this by encrypting the algorithms with a strong encryption technique. The Hacker demands a ransom to allow access to the asset and revert the control to the authorized organizations. Many individuals and Organizations have been victim to such Ransomware Attacks. With the mounting growth of technology, such attacks have increased exponentially and the need for adequate preventive techniques are also increasing. This paper reviews the current state-of-the-art Ransomware detection techniques implemented to resist such attacks. While most surveys focus on ransomware detection using Machine learning techniques, this survey concentrates on Ransomware techniques that apply the sub-domains of Artificial Intelligence. This paper reviews detection techniques that employ Machine Learning, Deep Learning and Natural Language Processing techniques, which are sub-fields of AI for ransomware detection. Though the reviewed works have good detection rates, a few open concerns are identified and discussed. The primary objective of the review is to highlight concerns of the proposed system that prevent it from becoming effective in real-time systems.