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A Multimodal Deep Learning Method for Android Malware Detection Using Various Features.

, , , , и . IEEE Trans. Inf. Forensics Secur., 14 (3): 773-788 (2019)

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Другие публикации лиц с тем же именем

Event-Driven Implicit Authentication for Mobile Access Control., , , и . NGMAST, стр. 248-255. IEEE, (2015)Runtime Detection Framework for Android Malware., , и . Mob. Inf. Syst., (2018)Binary executable file similarity calculation using function matching., , , и . J. Supercomput., 75 (2): 607-622 (2019)Rule Indexing for Efficient Intrusion Detection Systems., , , и . WISA, том 7115 из Lecture Notes in Computer Science, стр. 136-141. Springer, (2011)Weighted Harvest-Then-Transmit: UAV-Enabled Wireless Powered Communication Networks., , , , и . IEEE Access, (2018)Similarity calculation method for user-define functions to detect malware variants., , , , , и . RACS, стр. 236-241. ACM, (2014)Android malware classification method: Dalvik bytecode frequency analysis., , , и . RACS, стр. 349-350. ACM, (2013)A hybrid MAC protocol for optimal channel allocation in large-scale wireless powered communication networks., , , и . EURASIP J. Wireless Comm. and Networking, (2018)A Multimodal Deep Learning Method for Android Malware Detection Using Various Features., , , , и . IEEE Trans. Inf. Forensics Secur., 14 (3): 773-788 (2019)N-gram Opcode Analysis for Android Malware Detection., , , и . Int. J. Cyber Situational Aware., 1 (1): 231-255 (2016)