ICCDetector outputs a detection model after training with a set of benign apps and a set of malwares, and employs the trained model for malware detection. The performance of ICCDetector is evaluated with 5264 malwares, and 12026 benign apps.
Feb 3, 2016
ICCDetector: ICC-based malware detection on Android. (2016). IEEE Transactions on Information Forensics and Security. 11, (6), 1252-1264. Available at ...
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This system monitors various authorization-based features and events received by the Android applications and analyzes these characteristics using machine ...
Abstract—Most existing mobile malware detection methods. (e.g., Kirin and DroidMat) are designed based on the resources required by malwares (e.g., ...
This system monitors various authorization-based features and events received by the Android applications and analyzes these characteristics using machine ...
ICCDetector: ICC-Based Malware Detection on Android. IEEE Transactions on Information Forensics and Security, 11(6), 2016, 1252-1264. x. Page 16. Chapter 1.
Nov 23, 2022 · Detecting Android malware with static analysis, where the application is disassembled to be examined for the presence of any malicious code is a ...
With the use of a detection model trained on a collection of both good and bad applications, the permission-based technique ICCDetector [19] divides Android ...
A novel detection method based on deep learning is proposed to distinguish malware from trusted applications by treating one system call sequence as a ...
ABSTRACT. We present Apposcopy, a new semantics-based approach for identifying a prevalent class of Android malware that steals private user information.