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Obfuscated Malware Detection in IoT Android Applications Using Markov Images and CNN.

, , , , , , , , and . IEEE Syst. J., 17 (2): 2756-2766 (June 2023)

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Implementation and Evaluation of Measurement-Based Admission Control Schemes Within a Converged Networks QoS Management Framework.. CoRR, (2013)Improving dynamic analysis of android apps using hybrid test input generation., , and . Cyber Security, page 1-8. IEEE, (2017)Android Malware Detection Using Parallel Machine Learning Classifiers., , and . NGMAST, page 37-42. IEEE, (2014)N-gram Opcode Analysis for Android Malware Detection., , , and . Int. J. Cyber Situational Aware., 1 (1): 231-255 (2016)Deep Android Malware Detection., , , , , , , , , and 1 other author(s). CODASPY, page 301-308. ACM, (2017)Bot-IMG: A framework for image-based detection of Android botnets using machine learning., and . AICCSA, page 1-7. IEEE, (2021)Multi-Domain Network Traffic Analysis using Machine Learning and Deep Learning Techniques., , , , , , , , and . IC3, page 305-312. ACM, (2022)Continuous implicit authentication for mobile devices based on adaptive neuro-fuzzy inference system., , , and . Cyber Security, page 1-7. IEEE, (2017)Design and Implementation of a Measurement-Based Policy-Driven Resource Management Framework For Converged Networks., , , , and . CoRR, (2016)Semi-supervised novelty detection with one class SVM for SMS spam detection., and . IWSSIP, page 1-4. IEEE, (2022)