Malware Detection and Classification with Machine Learning Algorithms
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-97-1313-4_13
Reference23 articles.
1. Ahmed IT, Jamil N, Din MM, Hammad BT (2022) Binary and multi-class malware threads classification. Appl Sci (Switzerland) 12, 12
2. Alam MS, Vuong ST (2013) Random forest classification for detecting android malware. In: 2013 IEEE International conference on green computing and communications and IEEE Internet of Things and IEEE cyber, physical and social computing, pp 663–669
3. Aslan OA, Samet R (2020) A comprehensive review on malware detection approaches. IEEE Access 8:6249–6271
4. Assegie TA (2021) An optimized KNN model for signature-based malware detection
5. Bae S, Lee G, Im EG (2019) Ransomware detection using machine learning algorithms. Concurrency Comput: Pract Experience, 32:e5422, 06
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