Research on anti-spam e-mail filtering algorithm based on Bayesian

Computer Engineering and Applications ›› 2007, Vol. 43 ›› Issue (23): 174-176.

• 数据库与信息处理 • Previous Articles Next Articles

Research on anti-spam e-mail filtering algorithm based on Bayesian

LI Wen，LIU Pei-yu

School of Information Science and Engineering，Shandong Normal University，Ji’nan 250014，China

Received:1900-01-01 Revised:1900-01-01 Online:2007-08-11 Published:2007-08-11
Contact: LI Wen

基于贝叶斯的垃圾邮件过滤算法的研究

李雯，刘培玉

山东师范大学信息科学与工程学院，济南 250014

通讯作者: 李雯

Abstract

Abstract: Nowadays，the study on content-based spam filtering is one of the hot topics in the Internet security research area all over the world.And Bayesian classification method has expressed high accuracy.An improved algorithm based on Na?觙ve Bayesian and Boosting method is proposed in this paper.The experiment results show that the algorithm has better performance.

Key words: spam, e-mail filtering, Bayesian algorithm

摘要： 基于内容的垃圾邮件过滤问题是Internet安全技术研究的一个重点问题，而基于贝叶斯的分类方法在垃圾邮件处理上表现出了很高的准确度，因此受到了广泛的关注。在朴素贝叶斯算法的基础上，提出了一种基于最小风险贝叶斯方法同Boosting算法相结合的邮件过滤改进算法，提高了分类的精确度。实验证明，算法在邮件过滤中有更好的表现。

关键词: 垃圾邮件, 邮件过滤, 贝叶斯算法

LI Wen，LIU Pei-yu . Research on anti-spam e-mail filtering algorithm based on Bayesian[J]. Computer Engineering and Applications, 2007, 43(23): 174-176.

李雯，刘培玉. 基于贝叶斯的垃圾邮件过滤算法的研究[J]. 计算机工程与应用, 2007, 43(23): 174-176.

[1]	AN Weipeng, CHENG Xiaobo, LIU Yu. Application of Fleiss’ Kappa Coefficient in Bayesian Decision Tree Algorithm [J]. Computer Engineering and Applications, 2020, 56(7): 137-140.
[2]	QIU Ningjia, SHEN Zhuorui, WANG Hui, WANG Peng. Semi-supervised Learning Optimization Algorithm for Communication Spam Text Recognition [J]. Computer Engineering and Applications, 2020, 56(17): 121-128.
[3]	TAN Zhaowen, ZONG Rong, XI Xianqiang, WU Hao. QoS prediction based on Bayesian tensor decomposition [J]. Computer Engineering and Applications, 2018, 54(20): 74-79.
[4]	JING Shaoxue. Two-stage recursive Bayesian parameter identification algorithm with covariance resetting [J]. Computer Engineering and Applications, 2017, 53(6): 60-66.
[5]	MAN Yi, ZHANG Jiongmin, XU Xiaojin. OLAP cache mechanism based on naive Bayesian [J]. Computer Engineering and Applications, 2017, 53(6): 85-90.
[6]	YE Shiren, YE Renming, ZHU Mingfeng. Method to find spammer group for Weibo based on network relationship [J]. Computer Engineering and Applications, 2017, 53(6): 96-100.
[7]	XIA Huosong, LUO Pan, GAO Miaomiao. Filtering algorithm for SMS spam based on design science [J]. Computer Engineering and Applications, 2016, 52(19): 111-116.
[8]	CHEN Nian1，2, TANG Zhenmin2. Method of spam filtering online based on QBC active sampling learning algorithm [J]. Computer Engineering and Applications, 2014, 50(22): 170-174.
[9]	XUE Zhengyuan. Improved probability-based Bayesian anti-spam mechanism [J]. Computer Engineering and Applications, 2013, 49(7): 98-101.
[10]	HU Demin, Hu Jinlong. System design against spam message disguised with homonym [J]. Computer Engineering and Applications, 2013, 49(2): 92-96.
[11]	ZHAI Junchang1, QIN Yuping1, CHE Weiwei2. Feature words classification contribution applied in spam filtering [J]. Computer Engineering and Applications, 2012, 48(34): 116-119.
[12]	WANG Zuhui, JIANG Wei. Approach of improving incremental Bayes based spam filter by data amoothing [J]. Computer Engineering and Applications, 2012, 48(16): 21-25.
[13]	LI Shaomei，GUO Yunfei，CHEN Fucai. Research on SPIT detection [J]. Computer Engineering and Applications, 2011, 47(6): 11-14.
[14]	HUANG Jue1，CHEN Bing2，LIAO Changwu1. Improved artificial immune algorithm applied for spam filtering [J]. Computer Engineering and Applications, 2011, 47(30): 72-74.
[15]	WU Yeke1，WU Yingjie1，SONG Rushun1，CHEN Bo2. Spam filtering based on rough-LVQ network [J]. Computer Engineering and Applications, 2011, 47(26): 107-109.

Research on anti-spam e-mail filtering algorithm based on Bayesian

基于贝叶斯的垃圾邮件过滤算法的研究

PDF

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics