Acknowledgement
This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIT) (No. NRF-2022R1A4A1032361)
References
- PaloAltoNetworks, Unit42. "Ransomware Retrospective 2024: Unit 42 Leak Site Analysis". https://unit42.paloaltonetworks.com/unit-42-ransomware-leak-site-data-analysis/
- Koppen, Mario. "The curse of dimensionality." In proceedings of the 5th online world conference on soft computing in industrial applications (WSC5). Vol. 1. 2000.
- Mackiewicz, Andrzej, and Waldemar Ratajczak. "Principal components analysis (PCA)." Computers & Geosciences 19.3 (1993): 303-342. https://doi.org/10.1016/0098-3004(93)90090-R
- Kohavi, Ron, and George H. John. "Wrappers for feature subset selection." Artificial intelligence 97.1-2 (1997): 273-324 https://doi.org/10.1016/S0004-3702(97)00043-X
- Majd, Nahid Ebrahimi, and Torsha Mazumdar. "Ransomware Classification Using Machine Learning." In proceedings of the 2023 32nd International Conference on Computer Communications and Networks (ICCCN). IEEE, 2023
- Zhang, Bin, et al. "Ransomware classification using patch-based CNN and self-attention network on embedded N-grams of opcodes." Future Generation Computer Systems 110 (2020): 708-720. https://doi.org/10.1016/j.future.2019.09.025
- Masum, Mohammad, et al. "Ransomware classification and detection with machine learning algorithms." In proceedings of the 2022 IEEE 12th Annual Computing and Communication Workshop and Conference (CCWC). IEEE, 2022.
- Madani, Houria, et al. "Classification of ransomware using different types of neural networks." Scientific Reports 12.1 (2022): 4770.
- Guyon, Isabelle, et al. "Gene selection for cancer classification using support vector machines." Machine learning 46 (2002): 389-422. https://doi.org/10.1023/A:1012487302797
- Anaconda, Available: https://www.anaconda.com/
- RansomwareDetection, Available: https://github.com/mudimathur2020/RansomwareDetection