MalCertain: Enhancing Deep Neural Network Based Android Malware Detection by Tackling Prediction Uncertainty-Reference-Cited by-同舟云学术

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MalCertain: Enhancing Deep Neural Network Based Android Malware Detection by Tackling Prediction Uncertainty

Published:2024-04-12 Issue: Volume:14 Page:1-13
ISSN:
Container-title:Proceedings of the IEEE/ACM 46th International Conference on Software Engineering
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Author:

Li Haodong¹^ORCID,Xu Guosheng¹^ORCID,Wang Liu¹^ORCID,Xiao Xusheng²^ORCID,Luo Xiapu³^ORCID,Xu Guoai⁴^ORCID,Wang Haoyu⁵^ORCID

Affiliation:

1. Beijing University of Posts and Telecommunications, Beijing, China

2. Arizona State University, Tempe, Arizona, USA

3. The Hong Kong Polytechnic University, Hong Kong, China

4. Harbin Institute of Technology, Shenzhen, China

5. Huazhong University of Science and Technology, Hubei, China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3597503.3639122

Reference78 articles.

1. AndroZoo

2. AppBrain. 2022. "Number of Android Applications ". https://www.appbrain.com/stats..

3. Drebin: Effective and explainable detection of Android malware in your pocket;Arp Daniel;Ndss,2014

4. LUNA: Quantifying and Leveraging Uncertainty in Android Malware Analysis through Bayesian Machine Learning

5. Ensemble learning in Bayesian neural networks;Barber David;Nato ASI Series F Computer and Systems Sciences,1998

Cited by 1 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. Efficient and Generalized Image-Based CNN Algorithm for Multi-Class Malware Detection;IEEE Access;2024

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