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Context-Aware, Adaptive, and Scalable Android Malware Detection Through Online Learning.

, , , and . IEEE Trans. Emerg. Top. Comput. Intell., 1 (3): 157-175 (2017)

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Context-aware, Adaptive and Scalable Android Malware Detection through Online Learning (extended version)., , , and . CoRR, (2017)BinGo: cross-architecture cross-OS binary search., , , , , and . SIGSOFT FSE, page 678-689. ACM, (2016)Accurate and Scalable Cross-Architecture Cross-OS Binary Code Search with Emulation., , , and . IEEE Trans. Software Eng., 45 (11): 1125-1149 (2019)Exploring topic models to discern cyber threats on Twitter: A case study on Log4Shell., , , and . Intell. Syst. Appl., (November 2023)A multi-view context-aware approach to Android malware detection and malicious code localization., , , and . Empir. Softw. Eng., 23 (3): 1222-1274 (2018)Detection and classification of malicious JavaScript via attack behavior modelling., , , , , and . ISSTA, page 48-59. ACM, (2015)Context-Aware, Adaptive, and Scalable Android Malware Detection Through Online Learning., , , and . IEEE Trans. Emerg. Top. Comput. Intell., 1 (3): 157-175 (2017)graph2vec: Learning Distributed Representations of Graphs., , , , , and . CoRR, (2017)Evolvable simulations applied to Automated Red Teaming: A preliminary study., , , and . WSC, page 1444-1455. IEEE, (2010)Scalable analysis for malware and vulnerability detection in binaries. Nanyang Technological University, Singapore, (2018)