图 书 馆
数据驱动的恶意行为建模方法Data-Driven Approaches towards Malicious Behavior Modeling |
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| 课程网址: | http://videolectures.net/kdd2017_tutorial17_behavior_modeling/ |
| 主讲教师: | Christos Faloutsos; Srijan Kumar |
| 开课单位: | 卡内基梅隆大学 |
| 开课时间: | 2017-11-21 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | The safety, reliability and usability of web platforms are often compromised by malicious entities, such as vandals on Wikipedia, bot connections on Twitter, fake likes on Facebook, and several more. Computational models developed with large-scale real-world behavioral data have shown significant progress in identifying these malicious entities. This tutorial discusses three broad directions of state-of-the-art data-driven methods to model malicious behavior: (i) feature-based algorithms, in which distinguishing behavioral features are proposed to predict the malicious users; (ii) spectral-based algorithms, which have been widely used in settings of directed graphs, undirected graphs, and bipartite graphs such as "who-follows-whom" Twitter data and "who-likes-what" Facebook data; and (iii) density-based algorithms, which efficiently look for suspicious, highly-dense components in multi-dimensional behavioral data. This tutorial will introduce the details of the general algorithms from the above three classes that can be applied to any platform and dataset. |
| 关 键 词: | 数据驱动; 网络平台; 计算机科学 |
| 课程来源: | 视频讲座网 |
| 数据采集: | 2023-11-28：wujk |
| 最后编审: | 2023-11-28：wujk |
| 阅读次数: | 9 |