Mutual Information and Feature Importance Gradient Boosting: Automatic byte n‐gram feature reranking for Android malware detection-Reference-Cited by-同舟云学术

Mutual Information and Feature Importance Gradient Boosting: Automatic byte n‐gram feature reranking for Android malware detection

Published:2021-04-05 Issue: Volume: Page:
ISSN:0038-0644
Container-title:Software: Practice and Experience
language:en
Short-container-title:Softw Pract Exper

Author:

Yousefi‐Azar Mahmood¹²^ORCID,Varadharajan Vijay³,Hamey Len¹,Chen Shiping²

Affiliation:

1. Department of Computing, Faculty of Science and Engineering Macquarie University Sydney New South Wales Australia

2. Commonwealth Scientific and Industrial Research Organisation Data61 Sydney New South Wales Australia

3. Faculty of Engineering and Built Environment University of Newcastle Newcastle New South Wales Australia

Publisher

Wiley

Subject

Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/spe.2971

Reference55 articles.

1. AV test: facts and figures ‐ security report;2021https://www.av‐test.org/en/statistics/malware/. Accessed February 12 2021.

2. Android security & privacy 2018 year in review;2021.https://source.android.com/security/reports/Google_Android_Security_2018_Report_Final.pdf. Accessed February 12 2021.

3. WongMY LieD. IntelliDroid: a targeted input generator for the dynamic analysis of android malware. Paper presented at: Proceedings of the NDSS Symposium San Diego CA; vol. 16 2016:21‐24.

4. YangZ YangM ZhangY GuG NingP WangXS. Appintent: analyzing sensitive data transmission in android for privacy leakage detection. Paper presented at: Proceedings of the 2013 ACM SIGSAC Conference on Computer & Communications Security ACM New York NY United States;2013:1043‐1054.

5. ChistyakovA LobachevaE KuznetsovA RomanenkoA. Semantic embeddings for program behavior patterns;2018. arXiv preprint arXiv:1804.03635.

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Android Malware Detection in Bytecode Level Using TF-IDF and XGBoost;The Computer Journal;2023-01-22

2. Two-path Android Malware Detection Based on N-gram Feature Weighting;2022 4th International Conference on Information Technology and Computer Communications (ITCC);2022-06-23

3. Malware Detection Using Byte Streams of Different File Formats;IEEE Access;2022

4. Android Malware Detection with Classification Based on Hybrid Analysis and N-gram Feature Extraction;Advancements in Smart Computing and Information Security;2022