Detecting spam through their Sender Policy Framework records

被引:4
|
作者
Sipahi, Devrim [1 ]
Dalkilic, Gokhan [1 ]
Ozcanhan, Mehmet Hilal [1 ]
机构
[1] Dokuz Eylul Univ, Dept Comp Engn, Izmir, Turkey
关键词
email; Naive Bayes; Sender Policy Framework; spam;
D O I
10.1002/sec.1280
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Spamming has become one of the worst problems of email communication. Although various anti-spamming methods have been developed, because of creative spammers, none of them are able to stop the penetration of the innovated spam. The content-based anti-spam methods used for spam recognition require considerable amounts of computational resources. Therefore, less resource demanding methods are needed to match the growing number of spam. One example is network-based filtering, which is gaining importance. Sender Policy Framework (SPF) is a network protocol that can provide efficient network-based spam filtering. But, it is becoming evident that spammers have also started to manipulate SPF-based spam filtering. Presently, the spammers are purchasing domain names with SPF records to use them for sending spam. The only methods that can prevent such spam are the blacklist and content filtering techniques, or a blend of both. In the present study, the Domain Name System (DNS)/SPF records of spam-sending domain names are compared with nonspam-sending domain names, for improving SPF-based spam filtering. Research results show distinctive features between spam-sending and non-spam-sending domain names. Naive Bayes algorithmis utilized to identify spam-sending domain names. The time delay results of spam analysis shows that the devised SPF-based filtering offloads content filtering, significantly. Hence, our SPF-based method can act as a pre-filter that helps fighting spam. Copyright (C) 2015 John Wiley & Sons, Ltd.
引用
收藏
页码:3555 / 3563
页数:9
相关论文
共 50 条
  • [1] Enhanced Email Spam Prevention through Sender Verification Dual Models
    Limthanmaphon, Benchaphon
    Saraubon, Kobkiat
    [J]. INFORMATICS ENGINEERING AND INFORMATION SCIENCE, PT I, 2011, 251 : 343 - 354
  • [2] Spam filtering with sender authentication network
    Dalkilic, Gokhan
    Sipahi, Devrim
    [J]. COMPUTER COMMUNICATIONS, 2017, 98 : 72 - 79
  • [3] A Multi-classifier Framework for Detecting Spam and Fake Spam Messages in Twitter
    Raj, R. Jeberson Retna
    Srinivasulu, Senduru
    Ashutosh, Aldrin
    [J]. 2020 IEEE 9TH INTERNATIONAL CONFERENCE ON COMMUNICATION SYSTEMS AND NETWORK TECHNOLOGIES (CSNT 2020), 2020, : 266 - 270
  • [4] To block spam, demand sender authentication
    Matioc, M
    [J]. COMMUNICATIONS OF THE ACM, 2005, 48 (03) : 11 - 11
  • [5] Detecting Comment Spam through Content Analysis
    Huang, Congrui
    Jiang, Qiancheng
    Zhang, Yan
    [J]. WEB-AGE INFORMATION MANAGEMENT, 2010, 6185 : 222 - 233
  • [6] Fighting Spam on the Sender Side: A Lightweight Approach
    de Vries, Wouter Willem
    Moura, Giovane Cesar Moreira
    Pras, Aiko
    [J]. NETWORKED SERVICES AND APPLICATIONS - ENGINEERING, CONTROL AND MANAGEMENT, 2010, 6164 : 188 - 197
  • [7] Spam filter based on geographical location of the sender
    Caha, Tomas
    Kovarik, Martin
    [J]. JOURNAL OF ELECTRICAL ENGINEERING-ELEKTROTECHNICKY CASOPIS, 2022, 73 (04): : 292 - 298
  • [8] Detecting Spam WebPages through Topic and Semantics Analysis
    Wan, Jing
    Liu, Mufan
    Yi, Junkai
    Zhang, Xuechao
    [J]. 2015 GLOBAL SUMMIT ON COMPUTER & INFORMATION TECHNOLOGY (GSCIT), 2015,
  • [9] Identity Based Email Sender Authentication for Spam Mitigation
    Hameed, Sufian
    Kloht, Tobias
    Fu, Xiaoming
    [J]. 2013 EIGHTH INTERNATIONAL CONFERENCE ON DIGITAL INFORMATION MANAGEMENT (ICDIM), 2013, : 14 - 19
  • [10] An overview of the Sender Policy Framework (SPF) as an anti-phising mechanism
    Gorling, Stefan
    [J]. INTERNET RESEARCH, 2007, 17 (02) : 169 - 179