Guarding the Digital Frontier: A Logistic Regression Approach to Malware Detection
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-69986-3_6
Reference6 articles.
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2. Choudhary, S., Sharma, A.: Malware detection and classification using machine learning. In: 2020 International Conference on Emerging Trends in Communication, Control and Computing (ICONC3), pp. 1–4 (2020). https://doi.org/10.1109/ICONC345789.2020.9117547
3. Sun, J., Yan, K., Liu, X., Yang, C., Fu, Y.: Malware detection on android smartphones using keywords vector and SVM. In: 2017 IEEE/ACIS 16th International Conference on Computer and Information Science (ICIS), pp. 833–838 (2017). https://doi.org/10.1109/ICIS.2017.7960108
4. Yeo, M., et al.: Flow-based malware detection using convolutional neural network. In: 2018 International Conference on Information Networking (ICOIN), pp. 910–913 (2018). https://doi.org/10.1109/ICOIN.2018.8343255
5. Vinayakumar, R., Alazab, M., Soman, K.P., Poornachandran, P., Venkatraman, S.: Robust intelligent malware detection using deep learning. IEEE Access 7, 46717–46738 (2019). https://doi.org/10.1109/ACCESS.2019.2906934
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