A Clustering Techniques to Detect E-mail Spammer and Their Domains

被引：0

作者：

Patel, Kavita ^{[1
]}

Dubey, Sanjay Kumar ^{[1
]}

Singh, Ajay Shanker ^{[2
]}

机构：

[1] Amity Univ, CSE Dept, Sec 125, Noida, Uttar Pradesh, India

[2] Galgotias Univ, Sch CSE, Greater Noida, Uttar Pradesh, India

来源：

INFORMATION AND COMMUNICATION TECHNOLOGY FOR INTELLIGENT SYSTEMS (ICTIS 2017) - VOL 2 | 2018年 / 84卷

关键词：

Spam; Spam e-mail; Data mining; Clustering algorithms; Spam URL;

D O I：

10.1007/978-3-319-63645-0_71

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The latest internet has become a collaboration and communications platform, in that e-mail system is one of the most reliable internet services. Sending a spam e-mail is an economically useful commerce for intruders, with the very good earning of millions of dollars. The spam e-mail has become a critical issue to web and society, to stop/reduce the spam e-mails filtering techniques is not sufficient. This paper proposes to recognize spam domain by reading spam e-mails. These spam domains are nothing but Uniform Resource Locator (URL) of the website that intruder is promoting. The approach is based on extracting mail content; links from URL injected e-mail and subject of spam e-mails. These extracted parameters are grouped together through clustering algorithms and evaluated. This proposed work can be help as additional accessory to already available anti-spam tool to recognize intruders.

引用

页码：637 / 646

页数：10