图 书 馆
检测网络和主机异常的规则验证中的权重与修剪Weighting versus Pruning in Rule Validation for Detecting Network and Host Anomalies |
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| 课程网址: | http://videolectures.net/kdd07_tandon_wvpirv/ |
| 主讲教师: | Gaurav Tandon |
| 开课单位: | 佛罗里达理工学院 |
| 开课时间: | 2007-09-14 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | For intrusion detection, the LERAD algorithm learns a succinct set of comprehensible rules for detecting anomalies, which could be novel attacks. LERAD validates the learned rules on a separate held-out validation set and removes rules that cause false alarms. However, removing rules with possible high coverage can lead to missed detections. We propose to retain these rules and associate weights to them. We present three weighting schemes and our empirical results indicate that, for LERAD, rule weighting can detect more attacks than pruning with minimal computational overhead. |
| 关 键 词: | 入侵检测; LERAD算法加权方案 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-05-09：lxf |
| 阅读次数: | 36 |