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除了黑名单:学习要检测可疑的URL恶意网站

Beyond Blacklists: Learning to Detect Malicious Web Sites from Suspicious URLs
课程网址: http://videolectures.net/kdd09_ma_bbldmwssurl/  
主讲教师: Justin Ma
开课单位: 加州大学
开课时间: 2009-09-14
课程语种: 英语
中文简介:
恶意网站是互联网犯罪活动的基石。因此, 人们对开发防止最终用户访问此类网站的系统产生了广泛的兴趣。本文介绍了一种基于自动 url 分类的解决此问题的方法, 利用统计方法发现恶意网站 url 的词法和主机属性。这些方法能够通过提取和自动分析成千上万个可能指示可疑 url 的功能来学习高度预测的模型。生成的分类器获得95-99 的准确性, 从其 url 检测大量恶意网站, 只有少量误报。
课程简介: Malicious Web sites are a cornerstone of Internet criminal activities. As a result, there has been broad interest in developing systems to prevent the end user from visiting such sites. In this paper, we describe an approach to this problem based on automated URL classification, using statistical methods to discover the tell-tale lexical and host-based properties of malicious Web site URLs. These methods are able to learn highly predictive models by extracting and automatically analyzing tens of thousands of features potentially indicative of suspicious URLs. The resulting classifiers obtain 95-99% accuracy, detecting large numbers of malicious Web sites from their URLs, with only modest false positives.
关 键 词: 计算机科学; 数据挖掘; 安全和隐私
课程来源: 视频讲座网
最后编审: 2020-06-20:zyk
阅读次数: 53