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胡锡衡 《鞍山师范学院学报》2009,11(2):49-52
邮件过滤是反垃圾邮件的一种重要方法,其中基于邮件内容的过滤又是一种重要的、有效的过滤手段.基于电子邮件是一种半结构化的数据,并且,电子邮件中主要包括的是文本信息,因此,本文将文本挖掘的分类技术和方法引入到邮件过滤系统模型中,以实现对垃圾邮件的过滤. 相似文献
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梁雪松 《四川教育学院学报》2009,25(11):112-113,116
垃圾邮件的泛滥严重影响了电子邮件系统的正常运行,反垃圾邮件问题已经成为当前网络安全研究的重要课题。介绍了目前反垃圾邮件的主要方法,并提出了一种采用开源软件构建反垃圾邮件系统的解决方案。 相似文献
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Internet的迅速发展,电子邮件的应用变得十分广泛,但是许多无用、有害信息随之而来。通过对"垃圾邮件"的分析、处理,讨论了一种基于支持向量机的垃圾邮件识别方法,并进行了实验,实验结果表明支持向量机对垃圾邮件的识别是有效的。 相似文献
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Blogging has been an emerging media for people to express themselves. However, the presence of spam blogs (also known as splogs) may reduce the value of blogs and blog search engines. Hence, splog detection has recently attracted much attention from research. Most existing works on splog detection identify splogs using their content/link features and target on spam filters protecting blog search engines’ index from spam. In this paper, we propose a splog detection framework by monitoring the on-line search results. The novelty of our splog detection is that our detection capitalizes on the results returned by search engines. The proposed method therefore is particularly useful in detecting those splogs that have successfully slipped through the spam filters that are also actively generating spam-posts. More specifically, our method monitors the top-ranked results of a sequence of temporally-ordered queries and detects splogs based on blogs’ temporal behavior. The temporal behavior of a blog is maintained in a blog profile. Given blog profiles, splog detecting functions have been proposed and evaluated using real data collected from a popular blog search engine. Our experiments have demonstrated that splogs could be detected with high accuracy. The proposed method can be implemented on top of any existing blog search engine without intrusion to the latter. 相似文献
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黄文伟 《宁波广播电视大学学报》2009,7(3):69-72
垃圾邮件是网络世界的一大毒瘤。为了有效地控制垃圾邮件的蔓延,世界上许多国家纷纷制定了反垃圾邮件的法律。本文介绍了美国、欧盟、日本、澳大利亚以及我国规制垃圾邮件的有关法律制度,在此基础上通过比较分析对反垃圾邮件法律制度的设计进行了探讨。 相似文献
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David Ruano-Ordás Florentino Fdez-Riverola José R. Méndez 《Information processing & management》2018,54(2):303-317
One of the most relevant problems affecting the efficient use of e-mail to communicate worldwide is the spam phenomenon. Spamming involves flooding Internet with undesired messages aimed to promote illegal or low value products and services. Beyond the existence of different well-known machine learning techniques, collaborative schemes and other complementary approaches, some popular anti-spam frameworks such as SpamAssassin or Wirebrush4SPAM enabled the possibility of using regular expressions to effectively improve filter performance. In this work, we provide a review of existing proposals to automatically generate fully functional regular expressions from any input dataset combining spam and ham messages. Due to configuration difficulties and the low performance achieved by analysed schemes, in this work we introduce DiscoverRegex, a novel automatic spam pattern-finding tool. Patterns generated DiscoverRegex outperform those created by existing approaches (able to avoid FP errors) whilst minimising the computational resources required for its proper operation. DiscoverRegex source code is publicly available at https://github.com/sing-group/DiscoverRegex. 相似文献
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介绍了垃圾邮件的现状,以及目前常见的反垃圾邮件的方法。针对贝叶斯算法的特点,介绍使用贝叶斯过滤的方法实现垃圾邮件的过滤技术。 相似文献
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本文在介绍和分析贝叶斯理论的基础上,提出了贝叶斯算法和朴素贝叶斯分类器.并阐述了贝叶斯算法及朴素贝叶斯分类器在反垃圾邮件中的应用. 相似文献
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互联网的发展逐渐改变了人们的生活方式,电子邮件因其方便、快捷的特点已受到人们的青睐。但许多垃圾邮件同时也在网络中蔓延,占据了邮件服务器的大量存储空间,用户往往需要花费大量的时间去删除这些垃圾邮件。因此,研究邮件的自动过滤具有重要意义。邮件的自动过滤主要有基于规则和基于统计两种方式。而目前基于统计的过滤器中,常用的贝叶斯方法等是建立在经验风险最小化的基础之上,过滤器推广性能较差。支持向量机(SVM)是在统计学习理论的基础上发展而来的一种新的模式识别方法,在解决有限样本、非线性及高维模式识别问题中表现出许多特有的优势。它不仅考虑了对推广能力的要求,而且追求在有限信息的条件下得到最优结果。因此,本文将支持向量机应用于邮件过滤,实验证明过滤效果较好。 相似文献