CloudRPS: a cloud analysis based enhanced ransomware prevention system

Jeong Kyu Lee, Seo Yeon Moon, Jong Hyuk Park

Research output: Contribution to journalArticlepeer-review

45 Scopus citations

Abstract

Recently, indiscriminate ransomware attacks targeting a wide range of victims for monetary gains have become a worldwide social issue. In the early years, ransomware has used e-mails as attack method. The most common spreading method was through spam mail or harmful websites. In addition, social networking sites or smartphone messages are used. Ransomware can encrypt the user’s files and issues a warning message to the user and requests payment through bitcoin, which is a virtual currency that is hard to trace. It is possible to analyze ransomware but this has its limitations as new ransomware is being continuously created and disseminated. In this paper, we propose an enhanced ransomware prevention system based on abnormal behavior analysis and detection in cloud analysis system—CloudRPS. This proposed system can defend against ransomware through more in-depth prevention. It can monitors the network, file, and server in real time. Furthermore, it installs a cloud system to collect and analyze various information from the device and log information to defend against attacks. Finally, the goal of the system is to minimize the possibility of the early intrusion. And it can detect the attack quickly more to prevent at the user’s system in case of the ransomware compromises.

Original languageEnglish
Pages (from-to)3065-3084
Number of pages20
JournalJournal of Supercomputing
Volume73
Issue number7
DOIs
StatePublished - 1 Jul 2017

Keywords

  • Abnormal behavior
  • Cloud
  • Intrusion detection
  • Prevention system
  • Ransomware

Fingerprint

Dive into the research topics of 'CloudRPS: a cloud analysis based enhanced ransomware prevention system'. Together they form a unique fingerprint.

Cite this