A Feature Representation Method of Social Graph for Malware Detection
文献类型：会议论文
| 作者 | Jiang, Qingshan; Liu, Nancheng; Zhang, Wei |
| 出版日期 | 2013 |
| 会议名称 | 2013 4th Global Congress on Intelligent Systems, GCIS 2013 |
| 会议地点 | Hong Kong, China |
| 英文摘要 | The proliferation of malware has presented a serious threat to internet security, and made traditional signature-based methods unable to analyze and process the massive data timely and effectively. The development trend of malware motivates many research efforts in intelligent malware analysis, where machine learning is used for malware detection. Currently, most of machine learning methods on malware detection utilize file contents extracted from the file samples. However, besides file contents, relations among file samples can provide invaluable information about the properties of file samples, which may improve the malware detection accuracy. Social graph is a popular way to present a set of socially-relevant nodes connected by one or more relations. It can well present the relations/dependence among file samples. Therefore, we attempt to employ social graph to study the file relations as the feature representation of file samples, and combine machine learning methods to detect malware. |
| 收录类别 | EI |
| 语种 | 英语 |
| 源URL | [http://ir.siat.ac.cn:8080/handle/172644/4982]  |
| 专题 | 深圳先进技术研究院_医工所 |
| 作者单位 | 2013 |
| 推荐引用方式 GB/T 7714 | Jiang, Qingshan,Liu, Nancheng,Zhang, Wei. A Feature Representation Method of Social Graph for Malware Detection[C]. 见:2013 4th Global Congress on Intelligent Systems, GCIS 2013. Hong Kong, China. |
入库方式： OAI收割
来源：深圳先进技术研究院
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。