SVM with Gaussian kernel-based image spam detection on textual features

Prashant Kumar, M. Biswas
{"title":"SVM with Gaussian kernel-based image spam detection on textual features","authors":"Prashant Kumar, M. Biswas","doi":"10.1109/CIACT.2017.7977283","DOIUrl":null,"url":null,"abstract":"With the growth of the internet and the increasing importance of emails in our daily lives, spams have become a common phenomenon posing serious threats, as it gives rise to undesired emails. Image spam is a type of email spam in which the textual message is embedded within an image presenting it as a picture. This paper proposes a Support Vector Machine (SVM) with Gaussian kernel based classifier for detection of spam. In our experiment, we have used publicly available datasets with SVM with Gaussian kernel based classifier showing that our approach gives good performance over considered classifiers for measurement of F-measure, recall, accuracy and precision.","PeriodicalId":218079,"journal":{"name":"2017 3rd International Conference on Computational Intelligence & Communication Technology (CICT)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 3rd International Conference on Computational Intelligence & Communication Technology (CICT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIACT.2017.7977283","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 12

Abstract

With the growth of the internet and the increasing importance of emails in our daily lives, spams have become a common phenomenon posing serious threats, as it gives rise to undesired emails. Image spam is a type of email spam in which the textual message is embedded within an image presenting it as a picture. This paper proposes a Support Vector Machine (SVM) with Gaussian kernel based classifier for detection of spam. In our experiment, we have used publicly available datasets with SVM with Gaussian kernel based classifier showing that our approach gives good performance over considered classifiers for measurement of F-measure, recall, accuracy and precision.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于高斯核支持向量机的图像垃圾文本特征检测
随着互联网的发展和电子邮件在我们日常生活中的重要性日益增加,垃圾邮件已经成为一种普遍现象,造成严重的威胁,因为它会产生不受欢迎的电子邮件。图片垃圾邮件是一种电子邮件垃圾邮件,其中文本信息嵌入在图像中,呈现为图片。本文提出了一种基于高斯核的支持向量机分类器来检测垃圾邮件。在我们的实验中,我们将公开可用的数据集与SVM和基于高斯核的分类器一起使用,表明我们的方法在测量F-measure,召回率,准确性和精密度方面比考虑的分类器具有更好的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Smart solar tracking system for optimal power generation SVM with Gaussian kernel-based image spam detection on textual features Comparison between LDA & NMF for event-detection from large text stream data Research on the wisdom education platform of cloud computing architecture Robust TS fuzzy controller for helicopter via parallel distributed compensation
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1