Implementation of Decoy Deception based Detection System for Ransomware Attack
Article Sidebar
Main Article Content
Abstract
Ransomware poses a dangerous threat to cybersecurity. Data as well as rights owned by the user are adversely impacted. The situation has become considerably more critical as a result of the emergence of new ransomware varieties and Ransomware-as-a-Service. In this paper, we presented a novel deception-based and behaviour-based method for real-time ransomware detection. In order to avoid any loss before ransomware is discovered, we build pretend files and directories for nefarious behaviours. We conducted a pilot study using Locky, and the results demonstrate the effectiveness of our strategy with little system resource usage and geographical cost.
Article Details
References
James A. Sherer, Melinda L. McLellan, Emily R. Fedeles, and Nichole L. Sterling, “RANSOMWARE – PRACTICAL AND LEGAL CONSIDERATIONS FOR CONFRONTING THE NEW ECONOMIC ENGINE OF THE DARK WEB”, Richmond Journal of Law & Technology Volume XXIII, Issue 3
Dean F. Sittig, Hardeep Singh, “A Socio-technical Approach to Preventing, Mitigating, and Recovering from Ransomware Attacks”, Appl Clin Inform 2016; 7: 624–632 http://dx.doi.org/10.4338/ACI 2016-04-SOA-0064
Francesco Mercaldo, Vittoria Nardone, Antonella Santone, “Ransomware Inside Out”, 2016 11th International Conference on Availability, Reliability and Security, 978-1-5090-0990-9/16 $31.00 © 2016 IEEE DOI 10.1109/ARES.2016.35.
Sileshi Demesie Yalew1;2, Gerald Q. Maguire Jr.2, Seif Haridi2, Miguel Correia, “Hail to the Thief: Protecting Data from Mobile Ransomware with ransomSafeDroid”, 978-1-5386-1465-5/17/$31.00 c 2017 IEEE
Sajad Homayoun, Ali Dehghantanha, Marzieh Ahmadzadeh, Sattar Hashemi, Raouf Khayami, “Know Abnormal, Find Evil: Frequent Pattern Mining for
Ransomware Threat Hunting and Intelligence”, IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTING, 2168-6750 (c) 2017 IEEE
Eugene Kolodenkerz, William Koch, Gianluca Stringhiniy, and Manuel Egele, “PayBreak: Defense Against Cryptographic Ransomware”, 2017 ACM. ISBN 978-1-4503-4944-4/17/04
Monika , Pavol Zavarsky, Dale Lindskog, “Experimental Analysis of Ransomware on Windows and Android Platforms: Evolution and Characterization”, The 2nd International Workshop on Future Information Security, Privacy & Forensics for Complex Systems, Elsevier
Juan A. Herrera Silva, Myriam Hernández-Alvarez, “Large Scale Ransomware Detection by Cognitive Security”, 978-1-5386-3894- 1/17/$31.00 ©2017 IEEE
Aaron Zimba, Luckson Simukonda, Mumbi Chishimba, “Demystifying Ransomware Attacks: Reverse Engineering and Dynamic Malware Analysis of WannaCry for Network and Information Security”, ZAMBIA INFORMATION COMMUNICATION TECHNOLOGY (ICT) JOURNAL Volume 1 (Issue 1) (2017) Pages 35-40
Nolen Scaife, Henry Carter, Patrick Traynor, Kevin R.B. Butler,” CryptoLock (and Drop It): Stopping Ransomware Attacks on User Data”, 2016 IEEE 36th International Conference on Distributed Computing Systems
Shreya Chadha, Utham Kumar, “Ransomware: Let’s Fight Back!”, International Conference on Computing, Communication and Automation (ICCCA2017), ISBN: 978-1-5090-6471-7/17/$31.00 ©2017 IEEE.
Routa Moussaileb, Benjamin Bouget, Aurélien Palisse, Hélène Le Bouder, Nora Cuppens, Jean-Louis Lanet, “Ransomware’s Early Mitigation Mechanisms”, ACM ISBN 978-1-4503-6448-5/18/08. . . $15.00, https://doi.org/10.1145/3230833.3234691
Pratyush Raunak and Prabhakar Krishnan, “NETWORK DETECTION OF RANSOMWARE DELIVERED BY EXPLOIT KIT”, VOL. 12, NO. 12, JUNE 2017 ISSN 1819-6608 ARPN Journal of Engineering and Applied Sciences ©2006-2017 Asian Research Publishing Network
Manish Shukla, Sutapa Mondal, Sachin Lodha, “POSTER: Locally Virtualized Environment for Mitigating Ransomware Threat”, CCS’16 October 24-28, 2016, Vienna, Austria c 2016 Copyright held by the owner/author(s). ACM ISBN 978-1-4503-4139-4/16/10. DOI: http://dx.doi.org/10.1145/2976749.2989051.
Salunke, M.D., Kumbharkar, P.B., Kumar, P. “A Proposed Methodology to Mitigate the Ransomware Attack”, Advances in Parallel Computing, 2021, 39, pp. 16–21
Salunke, M., Kabra, R., & Kumar, A. (2015). IRJET-Layered architecture for DoS attack detection system by combine approach of Naive bayes and Improved K-mea Layered architecture for DoS attack detection system by combine approach of Naive bayes and Improved K-means Clustering Algorithm. International Research Journal of Engineering and Technology. www.irjet.net
Salunke, M., Kumbharkar, D. P. B., & Sharma, D. Y. K. (2020). A Proposed Methodology to Prevent a Ransomware Attack. International Journal of Recent Technology and Engineering (IJRTE), 9(1), 2723–2725. https://doi.org/10.35940/ijrte.a2860.059120