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Extensible Android Malware Detection and Family Classification Using Network-Flows and API-Calls., , and . ICCST, page 1-8. IEEE, (2019)Toward Developing a Systematic Approach to Generate Benchmark Android Malware Datasets and Classification., , , and . ICCST, page 1-7. IEEE, (2018)Android Botnets: What URLs are Telling Us., , and . NSS, volume 9408 of Lecture Notes in Computer Science, page 78-91. Springer, (2015)Dynamic Android Malware Category Classification using Semi-Supervised Deep Learning., , , , and . DASC/PiCom/CBDCom/CyberSciTech, page 515-522. IEEE, (2020)Towards a Network-Based Framework for Android Malware Detection and Characterization., , , , and . PST, page 233-234. IEEE Computer Society, (2017)Benchmarking Frameworks and Comparative Studies of Controller Area Network (CAN) Intrusion Detection Systems: A Review., , , and . CoRR, (2024)Using Streaming Data Algorithm for Intrusion Detection on the Vehicular Controller Area Network., , , and . UbiSec, volume 1557 of Communications in Computer and Information Science, page 131-144. Springer, (2021)Comparative Evaluation of Anomaly-Based Controller Area Network IDS., , , and . ICSCA, page 218-226. ACM, (2023)Understanding Android Financial MalwareAttacks: Taxonomy, Characterization, and Challenges., , and . J. Cyber Secur. Mobil., 7 (3): 1-52 (2018)Behavioral Analysis and Visualization of Fast-Flux DNS., , and . EISIC, page 250-253. IEEE Computer Society, (2012)