Ndagi et al., 2019
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| Wang et al. | Constructing features for detecting android malicious applications: issues, taxonomy and directions | |
| Mehtab et al. | AdDroid: rule-based machine learning framework for android malware analysis | |
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| Arora et al. | Minimizing network traffic features for android mobile malware detection | |
| Sato et al. | Detecting android malware by analyzing manifest files | |
| Varma et al. | Android mobile security by detecting and classification of malware based on permissions using machine learning algorithms | |
| Ndagi et al. | Machine learning classification algorithms for adware in android devices: a comparative evaluation and analysis | |
| Wang et al. | LSCDroid: Malware detection based on local sensitive API invocation sequences | |
| Bai et al. | $\sf {DBank} $ DBank: Predictive Behavioral Analysis of Recent Android Banking Trojans | |
| Rathore et al. | Detection of malicious android applications: Classical machine learning vs. deep neural network integrated with clustering | |
| KR101605783B1 (en) | Malicious application detecting method and computer program executing the method | |
| Du et al. | A static Android malicious code detection method based on multi‐source fusion | |
| Casolare et al. | Dynamic Mobile Malware Detection through System Call-based Image representation. | |
| Pavithra et al. | A comparative study on detection of malware and benign on the internet using machine learning classifiers | |
| Arslan et al. | A review on mobile threats and machine learning based detection approaches | |
| Han et al. | Identifying malicious Android apps using permissions and system events | |
| Waheed et al. | Effective and efficient android malware detection and category classification using the enhanced kronodroid dataset | |
| Li et al. | Novel Android Malware Detection Method Based on Multi-dimensional Hybrid Features Extraction and Analysis. | |
| Cilleruelo et al. | Malware detection inside app stores based on lifespan measurements | |
| Surendran et al. | Android malware detection based on informative syscall subsequences | |
| Prasad et al. | PermGuard: A Scalable Framework for Android Malware Detection Using Permission-to-Exploitation Mapping | |
| Deepserish et al. | PET-Droid: Android malware detection using static analysis | |
| Kalantari et al. | Browser Polygraph: Efficient Deployment of Coarse-Grained Browser Fingerprints for Web-Scale Detection of Fraud Browsers | |
| CN114282216A (en) | Malicious software detection method and device, computer equipment and storage medium | |
| Ojo et al. | Machine learning-based Android malware detection |