基于R语言的支持向量机在信息安全与垃圾邮件识别中的应用  

Application of Support Vector Machine in Information Security and Spam Identification Based on R Language

作　　者：朱伟明 ZHU Wei-ming(Guangdong Power Supply Bureau, Maoming Power Grid Co., Ltd., Maoming525000, Chin)

机构地区：[1]广东电网有限责任公司茂名供电局,广东茂名525000

出　　处：《机电工程技术》2016年第12期53-57,共5页Mechanical & Electrical Engineering Technology

摘　　要：随着垃圾邮件日益增多,准确识别并过滤垃圾邮件已成为互联网安全领域所重点关注的研究课题。回顾了近年来国内外垃圾邮件识别的相关研究成果,在此基础上利用开源统计软件R实现了垃圾邮件识别的SVM模型,并选取了不同的核函数做测试对比。实验结果表明,SVM可以比较准确地识别垃圾邮件,但今后还需在算法优化、样本特征选择上做改进。With the increasing number of spam, accurate identification and filtering of spam has become an important research topic in the field of Interact security. This paper reviews the relevant research results at home and abroad spam recognition in recent years, based on the open source R statistical software to achieve the SVM model of spam identification and selecting different kernel functions to do comparison test. The experimental results show that SVM can accurately identify spam, but in the future, it is necessary to improve the algorithm and the sample feature selection.

关 键 词：信息安全 垃圾邮件 模式识别 支持向量机 

分 类 号：TP309[自动化与计算机技术—计算机系统结构]