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A multi-view context-aware approach to Android malware detection and malicious code localization., , , and . Empir. Softw. Eng., 23 (3): 1222-1274 (2018)Adaptive and scalable Android malware detection through online learning., , , and . IJCNN, page 2484-2491. IEEE, (2016)Apk2vec: Semi-Supervised Multi-view Representation Learning for Profiling Android Applications., , , , and . ICDM, page 357-366. IEEE Computer Society, (2018)subgraph2vec: Learning Distributed Representations of Rooted Sub-graphs from Large Graphs., , , , and . CoRR, (2016)A Multi-view Context-aware Approach to Android Malware Detection and Malicious Code Localization., , , and . CoRR, (2017)LibSift: Automated Detection of Third-Party Libraries in Android Applications., , , , and . APSEC, page 41-48. IEEE Computer Society, (2016)Context-aware, Adaptive and Scalable Android Malware Detection through Online Learning (extended version)., , , and . CoRR, (2017)Contextual Weisfeiler-Lehman graph kernel for malware detection., , , , and . IJCNN, page 4701-4708. IEEE, (2016)Semantic modelling of Android malware for effective malware comprehension, detection, and classification., , , , , and . ISSTA, page 306-317. ACM, (2016)AdDetect: Automated detection of Android ad libraries using semantic analysis., , and . ISSNIP, page 1-6. IEEE, (2014)