Accurate mobile malware detection and classification in the cloud
Author:
Funder
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Subject
Multidisciplinary
Link
http://link.springer.com/content/pdf/10.1186/s40064-015-1356-1.pdf
Reference45 articles.
1. Aafer Y, Du W, Yin H (2013) DroidAPIMiner: mining API-Level Features for Robust Malware Detection in Android. In: International Conference on Security and Privacy in Communication Networks (SecureComm)
2. Afonso VM, de Amorim MF, Gregio, Junquera, de Geus (2014) Identifying android malware using dynamically obtained features. J Comp Virol Hacking Tech
3. Amos B, Turner HA, White J (2013) Applying machine learning classifiers to dynamic android malware detection at scale. In: International Conference on Wireless Communications and Mobile Computing (IWCMC)
4. Android Developers (2015) Monkey Runner. http://www.developer.android.com/tools/help/ monkeyrunner_concepts.html
5. Arp D, Spreitzenbarth M, Huebner M, Gascon H, Rieck K (2014) Drebin: efficient and explainable detection of android malware in your pocket. 21th Annual Network and Distributed System Security Symposium (NDSS)
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