Unravelling Obfuscated Malware Through Memory Feature Engineering and Ensemble Learning
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-9489-2_28
Reference12 articles.
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3. Nachreiner C et al (2021) Internet Security Report-Q3 2021 | WatchGuard Technologies. https://www.watchguard.com/wgrd-resource-center/security-report-q3-2021 (visited on 05/17/2022)
4. Bazrafshan Z et al (2013) A survey on heuristic malware detection techniques. In: The 5th conference on information and knowledge technology, 2013, pp 113–120. https://doi.org/10.1109/IKT.2013.6620049.
5. Mohanta A (2020) Malware analysis and detection engineering : a comprehensive approach to detect and analyze modern malware, 1st edn. Apress, New York. ISBN: 1-4842-6193-3
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