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Spam Image Clustering for Identifying Common Sources of Unsolicited Emails
2009
International Journal of Digital Crime and Forensics
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Spamming is a problem that affects people all over the world. Spam is an unsolicited email which has been sent to many people. ...
Spam images are sent for two reasons: 1) for advertisement purposes; 2) to hide the textual contents of an email from spam filters. ...
However, filters can only differentiate spam emails from nonspam emails but cannot tell the origins of spam. ...
doi:10.4018/jdcf.2009070101
fatcat:edrhfqfqkjfkhomxzzz4f76qui
Clustering Spam Campaigns with Fuzzy Hashing
2014
Proceedings of the AINTEC 2014 on Asian Internet Engineering Conference - AINTEC '14
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Simple methods looking for common identifiers in emails, such as URL or email addresses, are inefficient due to the emergence of obfuscation techniques like URL shortening. ...
In this paper we propose a new method based on fuzzy hashing to cluster spam with common goals into the same spam campaign. ...
as the corresponding spam emails contain common identifiers (e.g. ...
doi:10.1145/2684793.2684803
dblp:conf/aintec/ChenFKF14
fatcat:xoxtlslgobfmle24tsrqquky3a
A Multimodal Data Mining Framework for Revealing Common Sources of Spam Images
2009
Journal of Multimedia
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By identifying the common sources of spam images, we can provide evidence in tracking spam gangs. For this purpose, text recognition and visual feature extraction are performed. ...
This paper proposes a multimodal framework that clusters spam images so that ones from the same spam source/cluster are grouped together. ...
In this study, we go one step further to track down the common sources of the spam distributors based on spam image clustering. ...
doi:10.4304/jmm.4.5.313-320
fatcat:szbuvmrbqfeqjdgzqjpqwbktra
A Novel Approach towards Image Spam Classification
2011
Journal of clean energy technologies
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The gradient values are valuated for each pixel of an image. These obtained features are then normalized for efficient spam classification. ...
This unsolicited mails termed as spam occupy large storage space and bandwidth. Therefore designing an efficient spam filter is a challenging issue ahead for the future generation. ...
A multi-modal framework was put forth by Zhang et al. in [21] for revealing common sources of spam images. ...
doi:10.7763/ijcte.2011.v3.287
fatcat:vv4edrgpare67ds7emlyk5e2g4
Automated Spam Filtering through Data Mining Approach
2017
Sreyas International Journal of Scientists and Technocrats
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It is the need of the hour that these bulk unsolicited e-mails be effectively filtered. Increasing volume of these mails emphasizes on the requirement and design of dependable anti-spam filters. ...
For preventing the spam delivery, an automatic system based spam filter tool is employed. The objectives of spam filters and spam are contradicted diametrically. ...
Types of spam Based upon the source spam has different definitions. •Unsolicited bulk e-mail (UBE)-unsolicited e-mail, sent in large quantities. ...
doi:10.24951/sreyasijst.org/2017021004
fatcat:cfv33n7vhvejnh7anw733r22q4
A STUDY OF SPAM DETECTION ALGORITHM ON SOCIAL MEDIA NETWORKS
2014
Journal of Computer Science
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Therefore, this study attempts to review various spam detection frameworks which deals about the detection and elimination of spams in various sources. ...
The growing popularity of social networking sites has made them prime targets for spammers. ...
Also, he proposed a "Shingling Algorithm" which verifies the collected spam profile for content duplication like URL, image, comments and to accurately cluster spam and non-spam profile based on the features ...
doi:10.3844/jcssp.2014.2135.2140
fatcat:56u4f2hs75gdbl2w5yjyoagfym
A Study of Spam Detection Algorithm on Social Media Networks
[chapter]
2013
Advances in Intelligent Systems and Computing
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Therefore, this study attempts to review various spam detection frameworks which deals about the detection and elimination of spams in various sources. ...
The growing popularity of social networking sites has made them prime targets for spammers. ...
Also, he proposed a "Shingling Algorithm" which verifies the collected spam profile for content duplication like URL, image, comments and to accurately cluster spam and non-spam profile based on the features ...
doi:10.1007/978-81-322-1680-3_22
fatcat:zbmffnwkufabrp3d6a5dd444ei
Email Spam Classification using Hybridized Technique with Feature Selection
2016
IJARCCE
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Email has becomes the major source of communication these days. Majority of people are using this mode of communication for their personal or professional use. ...
So, it is very important to distinguish ham emails from spam emails, many methods have been proposed for classification of email as spam or ham emails. ...
They use Enron corpus dataset of text as well as image for experiment purpose. They uses Google's open source library called, Tasseract to extract words from images. ...
doi:10.17148/ijarcce.2016.51259
fatcat:yzbeg47d5fhypejukxnwpexqei
SMS spam filtering: Methods and data
2012
Expert systems with applications
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The paper also discusses the issues with data collection and availability for furthering research in this area, analyses a large corpus of SMS spam, and provides some initial benchmark results. ...
SMS spam filtering is a relatively new task which inherits many issues and solutions from email spam filtering. However it poses its own specific challenges. ...
When we compare these clusters to the types of spam identified by the GSMA (GSMA, 2011b), we find a close correspondence to the three main types which are described as, (i) SMS spam, where unsolicited ...
doi:10.1016/j.eswa.2012.02.053
fatcat:onkgyhoe45h3pi2bthtwlnc7ya
Digital Waste Sorting: A Goal-Based, Self-Learning Approach to Label Spam Email Campaigns
[chapter]
2015
Lecture Notes in Computer Science
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The main advantage of the proposed framework is that it can be used on large spam emails datasets, for which no prior knowledge is provided. ...
Fast analysis of correlated spam emails may be vital in the effort of finding and prosecuting spammers performing cybercrimes such as phishing and online frauds. ...
Unfortunately, emails are also the main vector for sending unsolicited bulks of messages, generally for commercial purpose, commonly known as spam. ...
doi:10.1007/978-3-319-24858-5_1
fatcat:s7x4flly45dttkp2z5sqe6j34y
Machine Learning Framework to Analyze Against Spear Phishing
2019
VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE
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We implemented different email classification algorithms on the datasets based on spam and ham emails where spear phishing methods are identified and implemented different classification and regression ...
threat the latest threat is intruded using the emails and major intrusion is done through spam emails. ...
Image spams are the kind of emails, the content or body of the message is displayed as a GIF or JPEG image. ...
doi:10.35940/ijitee.l3802.1081219
fatcat:v65cevq4ebhlxja5dfdx2tnysu
Overlapping Communities for Identifying Misbehavior in Network Communications
[chapter]
2014
Lecture Notes in Computer Science
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We show that mining the structural and temporal properties of email networks generated from Internet backbone traffic can be used to identify unsolicited email from the mixture of email traffic. ...
We also show that a link based community detection algorithm can separate legitimate and unsolicited email into distinct communities. ...
One of the applications which has been considered in this thesis is identifying the source of unsolicited email. ...
doi:10.1007/978-3-319-06608-0_33
fatcat:rpxzuu3gwnfj5bqyyxb5jo4pla
Suspended accounts in retrospect
2011
Proceedings of the 2011 ACM SIGCOMM conference on Internet measurement conference - IMC '11
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To perform our analysis, we identify over 1.1 million accounts suspended by Twitter for disruptive activities over the course of seven months. ...
Our results show that 77% of spam accounts identified by Twitter are suspended within on day of their first tweet. ...
We manually verify a sample of suspended accounts and find the vast majority were suspended for spamming, providing us with a rich source of ground truth for measuring spam. ...
doi:10.1145/2068816.2068840
dblp:conf/imc/ThomasGSP11
fatcat:pmmxrexyyfgdfnoymkelpqzjzu
Investigating the relationship between consumers' style of thinking and online victimization in scamming
2010
International Journal of Digital Content Technology and its Applications
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The rationale is to establish a foundation for the use of content analysis of unsolicited emails to offer insight into the possible relationship between a consumer's style of thinking and online victimization ...
This paper uses content analysis to identify the most frequent psychological tricks used in scamming and the most frequent flags which alert consumers to the illegitimate and unsolicited nature of the ...
Another study monitored the clustering behaviour of spammers in an effort to identify some anti-spam strategies (Li & Hsieh, 2006) . ...
doi:10.4156/jdcta.vol4.issue7.4
fatcat:mx24h3j55jerdhikgus6viw55y
Characterizing Spam traffic and Spammers
[article]
2010
arXiv
pre-print
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Other Versions
2007
2007 International Conference on Convergence Information Technology (ICCIT 2007)
unpublished
doi:10.1109/iccit.2007.89 fatcat:n5r2kwsm4bacliy7ypjkpqis2y
doi:10.1109/iccit.2007.89 fatcat:n5r2kwsm4bacliy7ypjkpqis2y
Spammers use common techniques to spam end users regardless of corporate server and public mail server. So we believe that our spam collection is a sample of world wide spam traffic. ...
We collected 400 thousand spam mails from a spam trap set up in a corporate mail server for a period of 14 months form January 2006 to February 2007. ...
In [4] presented a comprehensive study of clustering behavior of spammers and group based anti spam strategies. Their study exposed that the spammers has demonstrated clustering structures. ...
arXiv:1011.1050v1
fatcat:6ehy5afbj5a2lju5gva6fumkai
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