Exploring Feature Extraction and ELM in Malware Detection for Android Devices
文献类型：会议论文
| 作者 | Wei Zhang; Huan Ren; Qingshan Jiang; Kai Zhang |
| 出版日期 | 2015 |
| 会议名称 | the 12th International Symposium on Neural Networks (ISNN 2015) |
| 会议地点 | South Korea |
| 英文摘要 | A huge increase in the number of mobile malware brings a serious threat to Internet security, as the adoption rate of mobile device is soaring, especially Android device. A variety of researches have been developed to defense malware, but the mobile device users continuously suffer private information leak or economic losses from malware. Recently, a large number of methods have been proposed based on static or dynamic features analysis combining with machine learning methods, which are considered effective to detect malware on mobile device. In this paper, we propose an effective framework to detect malware on Android device based on feature extraction and neural network calssifier. In this framework, we take use of static features to represent malware and utilize extreme learning machine (ELM) algorithm to learn the neural network. We first extract features from the malware, and then utilize three different feature extraction methods including principal component analysis (PCA), Karhunen-Lo`eve transform (KLT) and independent component analysis (ICA) to transform the feature matrix into new feature spaces and generate three new feature matrixes. For each feature matrix, we construct En base classifiers by using ELM. Finally, we utilize Stacking method to combine the results. Experimental results suggest that the proposed framework is effective in detecting malware on Android device. |
| 收录类别 | EI |
| 语种 | 英语 |
| 源URL | [http://ir.siat.ac.cn:8080/handle/172644/7009]  |
| 专题 | 深圳先进技术研究院_数字所 |
| 作者单位 | 2015 |
| 推荐引用方式 GB/T 7714 | Wei Zhang,Huan Ren,Qingshan Jiang,et al. Exploring Feature Extraction and ELM in Malware Detection for Android Devices[C]. 见:the 12th International Symposium on Neural Networks (ISNN 2015). South Korea. |
入库方式： OAI收割
来源：深圳先进技术研究院
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