Institutional Repository
| secure machine learning, a brief overview | |
| Liao Xiaofeng; Ding Liping; Wang Yongji | |
| 2011 | |
| Conference Name | 2011 5th International Conference on Secure Software Integration and Reliability Improvement - Companion, SSIRI-C 2011 |
| Source | 2011 5th International Conference on Secure Software Integration and Reliability Improvement - Companion, SSIRI-C 2011 |
| Pages | 26-29 |
| Conference Date | 27-Jun-02 |
| Conference Place | Jeju Island, Korea, Republic of |
| Indexed Type | EI |
| Publish Place | United States |
| ISBN | 9780769544540 |
| Department | (1) National Engineering Research Center for Fundamental Software, Institute of Software, China; (2) State Key Laboratory of Computer Science, Institute of Software, China; (3) Graduate University, Chinese Academy of Sciences, Beijing 100049, China; (4) Information Engineering School, Nanchang University, Nanchang, Jiangxi, 330031, China |
| English Abstract | The purpose of this article is to give a brief overview on the current work towards the emerging research problem of secure machine learning. Machine learning technique has been applied widely in various applications especially in spam detection and network intrusion detection. Most existing learning schemes assume that the environment they settle in is benign. However this is not always true in the real adversarial decision-making situations where the future data sets and the training data set are no longer from the same population, due to the transformations employed by the adversaries. As more and more machine learning systems are put into use, it is imperative to consider the security of the machine learning system. As a emerging problem, it is attracting more and more researchers' attention. In this article, we present a brief overview on secure machine learning and current progress on developing secure machine learning algorithms. © 2011 IEEE. |
| Keyword | c (Programming Language) Intrusion Detection Learning Systems Population Statistics Software Reliability |
| Content Type | 会议论文 |
| URI | http://ir.iscas.ac.cn/handle/311060/14231 |
| Collection | 互联网软件技术实验室 |
| Recommended Citation GB/T 7714 | Liao Xiaofeng,Ding Liping,Wang Yongji. secure machine learning, a brief overview[C]. United States,2011:26-29. |
| Files in This Item: | ||||||
| File Name/Size | DocType | Version | Access | License | ||
| secure machine learn（207KB） | 开放获取 | -- | Application Full Text | |||
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