A TIME-ROBUST SPAM CLASSIFIER BASED ON BACK-PROPAGATION NEURAL NETWORKS AND BEHAVIOR-BASED FEATURES

机译：基于反向传播神经网络和行为特征的鲁棒垃圾邮件分类器

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Earlier works on detecting spam emails usually compare the contents of emails against specific keywords, which are not robust as the spammers frequently change the terms used in emails.In this paper, an back-propagation neural network is designed and implemented, which builds classification model by considering the behavior-based features revealed from emails' headers and syslogs.Since spamming behaviors are infrequently changed, compared with the change frequency of keywords used in spams, behavior-based features are more robust with respect to the change of time; so that the behavior-based filtering mechanism outperform keyword-based filtering.The experimental results indicate that our methods are more useful in distinguishing spam emails than that of keyword-based comparison.

机译：较早的检测垃圾邮件的工作通常将电子邮件的内容与特定的关键字进行比较，由于垃圾邮件发送者经常更改电子邮件中使用的术语，因此这种方法并不健壮。本文设计并实现了一种反向传播神经网络，它建立了分类模型由于不经常更改垃圾邮件的行为，因此与垃圾邮件中使用的关键字的更改频率相比，基于行为的功能相对于时间的变化更稳定。实验结果表明，与基于关键字的比较相比，我们的方法在区分垃圾邮件方面更有用。

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来源
《Proceedings of the 2007 International Conference on Machine Learning and Cybernetics》|2007年|P.2245-2250|共6页
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CHIH-HUNG WU; CHIUNG-HUI TSAI;
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中图分类计算技术、计算机技术;
关键词
Spam; Back-Propagation Neural Networks; Machine Learning; Classification;

机译：垃圾邮件;反向传播神经网络;机器学习;分类;

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专利

1. Robust classification for spam filtering by back-propagation neural networks using behavior-based features [J] . Chih-Hung Wu, Chiung-Hui Tsai Applied Intelligence . 2009,第2期

机译：使用基于行为的特征通过反向传播神经网络对垃圾邮件过滤进行可靠分类
2. Robust classification for spam filtering by back-propagation neural networks using behavior-based features [J] . Wu CH, Tsai CH Applied Intelligence: The International Journal of Artificial Intelligence, Neural Networks, and Complex Problem-Solving Technologies . 2009,第2期

机译：使用基于行为的功能通过反向传播神经网络对垃圾邮件过滤进行可靠分类
3. Behavior-based Spam Detection Using A Hybrid Method Of Rule-based Techniques And Neural Networks [J] . Chih-Hung Wu Expert systems with applications . 2009,第3p1期

机译：基于规则技术和神经网络混合方法的基于行为的垃圾邮件检测
4. A TIME-ROBUST SPAM CLASSIFIER BASED ON BACK-PROPAGATION NEURAL NETWORKS AND BEHAVIOR-BASED FEATURES [C] . CHIH-HUNG WU, CHIUNG-HUI TSAI International Conference on Machine Learning and Cybernetics . 2007

机译：基于反向传播神经网络和基于行为的特征的时间强大的垃圾邮件分类器
5. An application of Artificial Neural Networks to forecast winning price: A comparison of Back-Propagation Networks and Adaptive Network-Based Fuzzy Inference Systems. [D] . Lin, Yingchih. 2010

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7. Research on Spam Classifier Based on Features of Spammer`s Behaviours [O] . Liu Zhen, Tan Liang, Zhou Ming-Tian 2007

机译：基于垃圾邮件机构的特征的垃圾邮件分类器研究
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A TIME-ROBUST SPAM CLASSIFIER BASED ON BACK-PROPAGATION NEURAL NETWORKS AND BEHAVIOR-BASED FEATURES

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