LSTM-Based Hierarchical Denoising Network for Android Malware Detection
Mobile security is an important issue on Android platform. Most malware detection methods based on machine learning models heavily rely on expert knowledge for manual feature engineering, which are still difficult to fully describe malwares. In this paper, we present LSTM-based hierarchical denoise...
Main Authors: | Jinpei Yan, Yong Qi, Qifan Rao |
---|---|
Format: | Article |
Language: | English |
Published: |
Hindawi-Wiley
2018-01-01
|
Series: | Security and Communication Networks |
Online Access: | http://dx.doi.org/10.1155/2018/5249190 |
Similar Items
-
Detecting Malware with an Ensemble Method Based on Deep Neural Network
by: Jinpei Yan, et al.
Published: (2018-01-01) -
Android Malware Analysis Based on System Call sequences and Attention-LSTM
by: Po-Yen Tseng, et al.
Published: (2019) -
Android malware detection using network-based approaches
by: Alfs, Emily
Published: (2018) -
Trends In Android Malware Detection
by: Kaveh Shaerpour, et al.
Published: (2013-09-01) -
A Hierarchical Approach for Android Malware Detection Using Authorization-Sensitive Features
by: Hui Chen, et al.
Published: (2021-02-01)