Research on Data Drift and Class Imbalance in Android Malware Detection-Reference-Cited by-同舟云学术

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Research on Data Drift and Class Imbalance in Android Malware Detection

Published:2024 Issue: Volume: Page:429-444
ISSN:1867-8211
Container-title:Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
language:en
Short-container-title:

Author:

Liu Zhen^ORCID,Wang Ruoyu^ORCID,Peng Bitao^ORCID,Wang Changji^ORCID,Gan Qingqing^ORCID

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-63989-0_22

Reference28 articles.

1. Statcounter: Mobile operating system’s market share worldwide (2022). https://gs.statcounter.com/os-market-share/mobile/worldwide. Accessed 26 Dec 2022

2. Statista: Number of apps available in leading app stores (2022). https://www.statista.com/statistics/289418/number-of-available-apps-in-the-google-play-store-quarter/. Accessed 26 Dec 2022

3. Crowdstrike: What is mobile malware? (2022) https://www.crowdstrike.com/cybersecurity-101/malware/mobile-malware/. Accessed 26 Dec 2022

4. Guo, Y., Yan, Q.: Android malware adversarial attacks based on feature importance prediction. Int. J. Mach. Learn. Cybern. 2022, 1–11 (2022)

5. Sharma, T., Rattan, D.: Malicious application detection in android-A systematic literature review. Comput. Sci. Rev. 40, 100373 (2021)

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