Cryptographic Ransomware Encryption Detection: Survey: Author’s Declaration


Authors:

(1) Kenan Begovic, currently a Ph.D. candidate in Computer Science at Qatar University. He received his MS in Information and Computer Security from University of Liverpool;

(2) Abdulaziz Al-Ali ,received the Ph.D. degree in machine learning from the University of Miami, FL, USA, in 2016 and he is currently an Assistant Professor in the Computer Science and Engineering Department, and director of the KINDI Center for Computing Research at Qatar University;

(3) Qutaibah Malluhi, a Professor at the Department of Computer Science and Engineering at Qatar University (QU).

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

CRediT authorship contribution statement

Kenan Begovic: Conceptualization, Methodology, Formal analysis, Resources, Writing – original draft, Writing – review & editing. Abdulaziz Al-Ali: Conceptualization, Validation, Writing – review & editing, Supervision. Qutaibah Malluhi: Conceptualization, Validation, Writing – review & editing, Supervision.

Data availability

No data was used for the research described in the article.

References

Almashhadani, A.O., Kaiiali, M., Sezer, S., O’Kane, P., 2019. A multi-classifier networkbased crypto ransomware detection system: a case study of Locky ransomware. IEEE Access 7, 47053–47067. doi:10.1109/ACCESS.2019.2907485.

A Targeted Campaign Break-Down – Ryuk Ransomware. Check Point Research 2018. https://research.checkpoint.com/2018/ryuk-ransomware-targetedcampaign-break/(accessed December 9, 2021).

Adamov, A., Carlsson, A., Surmacz, T., 2019. An analysis of lockergoga ransomware. In: 2019 IEEE East-West Design & Test Symposium (EWDTS). IEEE, pp. 1–5.

Ahmed, Y.A., Koçer, B., Huda, S., Saleh Al-rimy, B.A., Hassan, M.M., 2020. A system call refinement-based enhanced Minimum Redundancy Maximum Relevance method for ransomware early detection. J. Netw. Comput. Appl. 167, 102753. doi:10.1016/j.jnca.2020.102753.

Aidan, J.S., Verma, H.K., Awasthi, L.K., 2017. Comprehensive survey on petya ransomware attack. In: 2017 International Conference on Next…

Source…