DaDiDroid: An Obfuscation Resilient Tool for Detecting Android Malware via Weighted Directed Call Graph Modelling-Reference-Cited by-同舟云学术

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DaDiDroid: An Obfuscation Resilient Tool for Detecting Android Malware via Weighted Directed Call Graph Modelling

Published:2019 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 16th International Joint Conference on e-Business and Telecommunications
language:
Short-container-title:

Author:

Ikram Muhammad¹,Beaume Pierrick²,Kaafar Mohamed³

Affiliation:

1. Macquarie University, Australia, University of Michigan and U.S.A., --- Select a Country ---

2. Data61 CSIRO and Australia, --- Select a Country ---

3. Macquarie University, Australia, Data61 CSIRO and Australia, --- Select a Country ---

Publisher

SCITEPRESS - Science and Technology Publications

Cited by 22 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. Practical Attacks Against DNS Reputation Systems;2024 IEEE Symposium on Security and Privacy (SP);2024-05-19

2. PermDroid a framework developed using proposed feature selection approach and machine learning techniques for Android malware detection;Scientific Reports;2024-05-10

3. ObfusGate: Representation Learning-Based Gatekeeper for Hardware-Level Obfuscated Malware Detection;2024 Design, Automation & Test in Europe Conference & Exhibition (DATE);2024-03-25

4. Intelligent Chain: A Safer Decision-Making Framework with Blockchain-Based Incentives;Journal of Applied Security Research;2023-11-30

5. Experimental comparison of features, analyses, and classifiers for Android malware detection;Empirical Software Engineering;2023-09-26

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