Ransomware Detection, Avoidance, and Mitigation Scheme: A Review and Future Directions

Adhirath Kapoor, Ankur Gupta, Rajesh Gupta, Sudeep Tanwar, Gulshan Sharma and Innocent E. Davidson
Additional contact information
Adhirath Kapoor: Model Institute of Engineering and Technology (Autonomous), Jammu 181122, India
Ankur Gupta: Model Institute of Engineering and Technology (Autonomous), Jammu 181122, India
Rajesh Gupta: Department of Computer Science and Engineering, Institute of Technology, Nirma University, Ahmedabad 382481, India
Sudeep Tanwar: Department of Computer Science and Engineering, Institute of Technology, Nirma University, Ahmedabad 382481, India
Gulshan Sharma: Department of Electrical Power Engineering, Steve Biko Campus, Durban University of Technology, Durban 4001, South Africa
Innocent E. Davidson: Department of Electrical Power Engineering, Steve Biko Campus, Durban University of Technology, Durban 4001, South Africa

Sustainability, 2021, vol. 14, issue 1, 1-24

Abstract: Ransomware attacks have emerged as a major cyber-security threat wherein user data is encrypted upon system infection. Latest Ransomware strands using advanced obfuscation techniques along with offline C2 Server capabilities are hitting Individual users and big corporations alike. This problem has caused business disruption and, of course, financial loss. Since there is no such consolidated framework that can classify, detect and mitigate Ransomware attacks in one go, we are motivated to present Detection Avoidance Mitigation (DAM), a theoretical framework to review and classify techniques, tools, and strategies to detect, avoid and mitigate Ransomware. We have thoroughly investigated different scenarios and compared already existing state of the art review research against ours. The case study of the infamous Djvu Ransomware is incorporated to illustrate the modus-operandi of the latest Ransomware strands, including some suggestions to contain its spread.

Keywords: Ransomware; cryptography; WannaCry; Djvu; malware; Ransomware detection (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://www.mdpi.com/2071-1050/14/1/8/pdf (application/pdf)
https://www.mdpi.com/2071-1050/14/1/8/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:14:y:2021:i:1:p:8-:d:707240

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().