Design and Implementation of an Automated APK Analysis System for Practical Forensics
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-9239-3_36
Reference8 articles.
1. Wang, X.: Research on Malware Detection Technology for Mobile Smart Terminals Based on Behavioral Sequences. Guangzhou University (2022).https://doi.org/10.27040/d.cnki.ggzdu.2022.0011-22
2. Zhang, K.: Research on Multi-features Based Approach for Android Malware Hybrid Analysis and Detection. University of Electronic Science and Technology (2021).https://doi.org/10.27005/d.cnki.gdzku.2021.002850
3. Lu, J.: Research and Implementation of Automatic Detection Method for Android Malicious Applications. Beijing University of Posts and Telecommunications (2021). https://doi.org/10.26969/d.cnki.gbydu.2021.001458
4. Enck, W., Gilbert, P., Han, S., et al.: TaintDroid. ACM Trans. Comput. Syst. 32(2), 1–29 (2014)
5. Andriatsimandefitra, R., Tong, V.V.T.: Detection and identification of android malware based on information flow monitoring. In: 2015 IEEE 2nd International Conference on Cyber Security and Cloud Computing (CSCIoud), pp. 200–203. IEEE (2015)
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