Ransomware Prevention System Design based on File Symbolic Linking Honeypots
Danyil Zhuravchak, Taras Ustyianovych, Valeriy Dudykevych, Bogdan Venny, Khrystyna Ruda · 2021 11th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS) · 2021
The data-driven period produces more and more security-related challenges that even experts can hardly deal with. One of the most complex threats is ransomware, which is very taxing and devastating to detect and mainly prevent. Our research methods showed significant results in identifying ransomware processes using the honeypot concept augmented with symbolic linking to reduce damage made to the file system. The CIA (confidentiality, integrity, availability) metrics have been adhered to. We propose to optimize the malware process termination procedure and introduce an artificial intelligence-human collaboration to enhance ransomware classification and detection.