TWC: Small: Unsupervised and Statistical Natural Language Processing Techniques for Automatic Phishing and Opinion Spam Detection

在网络钓鱼中，攻击者试图从互联网用户那里窃取敏感信息，例如银行/信用卡帐号、登录信息等。美国社会和经济越来越依赖互联网和网络，而网络钓鱼正困扰着美国。一种流行的钓鱼方法是创建一个模仿好网站的网站，然后通过电子邮件吸引用户访问，这是迄今为止最流行的吸引毫无戒心的用户访问钓鱼网站的媒介。由于这种工作方式和钓鱼所造成的损害，设计高效和有效的电子邮件和网站分类器是很重要的。在这个项目中，受自然语言处理方法的启发，正在设计用于钓鱼电子邮件和网站检测的新技术。然后在真实的数据集上严格地实施和验证它们。它们还应用于观点垃圾邮件的自动检测。预计拟议的研究将：(I)有助于推动自然语言处理技术的极限，(Ii)产生这些技术在网络安全中的新应用。过去，和平协会非常成功地让妇女和少数群体，包括代表人数不足的少数群体参与他的研究，这一努力将在这个项目中继续下去。休斯顿大学一直被认为是一所为拉美裔美国人服务的机构，PI将继续他过去成功的努力，让包括非裔美国人和西班牙裔美国人在内的代表不足的少数族裔参与这项研究。这项研究将进入课堂，并通过网络上的出版物和软件广泛传播。

In phishing, an attacker tries to steal sensitive information, e.g., bank/credit card account numbers, login information, etc., from Internet users. The US society and economy are increasingly dependent on the Internet and the web, which is plagued by phishing. One popular phishing method is to create a site that mimics a good site and then attract users to it via email, which is by far the most popular medium to entice unsuspecting users to the phishing site. Because of this modus operandi and the damages caused by phishing, it is important to design efficient and effective classifiers for emails and web sites. In this project, new techniques, inspired from natural language processing methods, are being designed for phishing email and web site detection. They are then implemented and validated rigorously on realistic data sets. They are also applied to automatic detection of opinion spam. Proposed research is expected to: (i) be useful in pushing the envelope of natural language processing techniques, and (ii) yield new applications of these techniques in cyber security. In the past, the PI has been very successful in involving women and minorities including underrepresented minorities in his research and this effort will be continued in this project. University of Houston has been recognized as a Hispanic-serving institution and the PI will continue his past successful efforts to involve underrepresented minorities including African Americans and Hispanics in this research. This research will be moved into the classroom and broadly disseminated through publications and software on the web.