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Efficient Android Malware Detection Using API Rank and Machine Learning.

, , , , and . J. Internet Serv. Inf. Secur., 9 (1): 48-59 (2019)

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RGBDroid: A Novel Response-Based Approach to Android Privilege Escalation Attacks., , , , , , and . LEET, USENIX Association, (2012)Comparison of Tie-Breaking Policies for Real-Time Scheduling on Multiprocessor., , , , and . EUC, volume 3207 of Lecture Notes in Computer Science, page 174-182. Springer, (2004)A New Technique for Detecting Android App Clones Using Implicit Intent and Method Information., , , , , and . ICUFN, page 478-483. IEEE, (2019)A remotely controlled out-pipe climbing robot., , and . URAI, page 126. IEEE, (2013)Android malware detection using convolutional neural networks and data section images., , , , , and . RACS, page 149-153. ACM, (2018)Automotive digital forensics through data and log analysis of vehicle diagnosis Android apps., , , and . Forensic Sci. Int. Digit. Investig., (2024)Machine learning-based software classification scheme for efficient program similarity analysis., , , , , and . RACS, page 114-118. ACM, (2015)Runtime Input Validation for Java Web Applications using Static Bytecode Instrumentation., , , , , and . RACS, page 148-152. ACM, (2016)A Static Birthmark of Windows Binary Executables Based on Strings., , , , , , and . IMIS, page 734-738. IEEE Computer Society, (2013)Measuring similarity of android applications via reversing and K-gram birthmarking., , , , , , , and . RACS, page 336-341. ACM, (2013)