An Android Malware Multi-class Classification Explained Through Genetic Programming

Author:

D’Angelo GianniORCID,Palmieri FrancescoORCID,Robustelli AntonioORCID

Publisher

Springer Nature Switzerland

Reference34 articles.

1. Abderrahmane, A., Adnane, G., Yacine, C., Khireddine, G.: Android malware detection based on system calls analysis and cnn classification. In: 2019 IEEE Wireless Communications and Networking Conference Workshop (WCNCW), pp. 1–6 (2019). https://doi.org/10.1109/WCNCW.2019.8902627

2. D’Angelo, G., Della-Morte, D., Pastore, D., Donadel, G., De Stefano, A., Palmieri, F.: Identifying patterns in multiple biomarkers to diagnose diabetic foot using an explainable genetic programming-based approach. Future Gener. Comput. Syst. 140, 138–150 (2023). https://doi.org/10.1016/j.future.2022.10.019. https://www.sciencedirect.com/science/article/pii/S0167739X2200334X

3. D’Angelo, G., Farsimadan, E., Ficco, M., Palmieri, F., Robustelli, A.: Privacy-preserving malware detection in android-based iot devices through federated markov chains. Future Gener. Comput. Syst. 148, 93–105 (2023). https://doi.org/10.1016/j.future.2023.05.021. https://www.sciencedirect.com/science/article/pii/S0167739X23002054

4. D’Angelo, G., Ficco, M., Palmieri, F.: Malware detection in mobile environments based on autoencoders and api-images. J. Parallel Distrib. Comput. 137, 26–33 (2020). https://doi.org/10.1016/j.jpdc.2019.11.001. https://www.sciencedirect.com/science/article/pii/S0743731519302436

5. D’Angelo, G., Ficco, M., Palmieri, F.: Association rule-based malware classification using common subsequences of api calls. Appl. Soft Comput. 105, 107234 (2021). https://doi.org/10.1016/j.asoc.2021.107234. https://www.sciencedirect.com/science/article/pii/S1568494621001575

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