Evading Static and Dynamic Android Malware Detection Mechanisms

Author:

John Teenu S.,Thomas Tony

Publisher

Springer Singapore

Reference54 articles.

1. A guide to malware detection techniques and beyond. https://www.cynet.com/blog/a-guide-to-malware-detection-techniques-av-ngav-and-beyond/. Accessed 08 Sept 2020

2. Machine learning methods for malware detection. https://media.kaspersky.com/en/enterprise-security/Kaspersky-Lab-Whitepaper-Machine-Learning.pdf. Accessed 08 Oct 2020

3. Mcafee mobile threat report 2020. https://www.mcafee.com/content/dam/consumer/en-us/docs/2020-Mobile-Threat-Report.pdf. Accessed 08 Sept 2020

4. Securing against malware using artificial intelligence. https://www.nortonlifelock.com/blogs/feature-stories/securing-against-malware-using-artificial-intelligence. Accessed 08 Oct 2020

5. Abaid, Z., Kaafar, M.A., Jha, S.: Quantifying the impact of adversarial evasion attacks on machine learning based android malware classifiers. In: 2017 IEEE 16th International Symposium on Network Computing and Applications (NCA), pp. 1–10. IEEE (2017)

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