Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Software
Reference48 articles.
1. Aalst van der, W. M. P. (2016). Process Mining - Data Science in Action, Second Edition. Springer 2016, ISBN 978-3-662-49850-7, pp. 3-452.
2. Aafer, Y., Du, W., Hin, Y. (2013). Droidapiminer: Mining api-level features for robust malware detection in android. In T. Zia, A. Zomaya, V. Varadharajan, & M. Mao (Eds.), Security and privacy in communication networks (pp. 86–103). Springer International Publishing.
3. Alazab, M. (2015). Profiling and classifying the behavior of malicious codes. Journal of Systems and Software, 100, 91–102.
4. Ardimento, P., Aversano, L., Bernardi, M. L., Cimitile, M. (2020). Data-aware declarative process mining for malware detection. In 2020 International Joint Conference on Neural Networks, IJCNN 2020, Glasgow, United Kingdom, July 19-24, 2020, pages 1–8. IEEE, 2020.
5. Arora, A., Garg, S., Peddoju, S. K. (2014). Malware detection using network traffic analysis in android based mobile devices. In Next Generation Mobile Apps, Services and Technologies (NGMAST), 2014 Eighth International Conference on, pages 66–71.
Cited by
2 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献