Application of Machine Learning Algorithms for Android Malware Detection-Reference-Cited by-同舟云学术

Application of Machine Learning Algorithms for Android Malware Detection

Published:2018 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2018 International Conference on Computational Intelligence and Intelligent Systems - CIIS 2018
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Author:

Kakavand Mohsen¹,Dabbagh Mohammad¹,Dehghantanha Ali²

Affiliation:

1. School of Science & Technology, Sunway University, Kuala Lumpur, Malaysia

2. School of Computer Science, University of Guelph, Ontario, Canada

Publisher

ACM Press

Reference15 articles.

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2. R. Unuchek, "Mobile malware evolution 2017," Kaspersky Lab, 2018. [Online]. Available: https://securelist.com/mobile-malware-review-2017/84139/.

3. M. Kakavand, N. Mustapha, A. Mustapha, M. T. Abdullah, and H. Riahi, "Issues and Challenges in Anomaly Intrusion Detection for HTTP Web Services," J. Comput. Sci., vol. 11, no. 11, pp. 1041--1053, 2015.

4. N. Milosevic, A. Dehghantanha, and K. K. R. Choo, "Machine learning aided Android malware classification," Comput. Electr. Eng., vol. 0, pp. 1--9, 2017.

5. M. Zhang, Y. Duan, H. Yin, and Z. Zhao, "Semantics-Aware Android Malware Classification Using Weighted Contextual API Dependency Graphs," in Proceeding CCS '14 Proceedings of the 2014 ACM SIGSAC Conference on Computer and Communications Security, 2014.

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