Proceedings ArticleDOI
Evaluation of spam detection and prevention frameworks for email and image spam: a state of art
Pedram Hayati,Vidyasagar Potdar +1 more
- pp 520-527
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This paper aims to analyse existing works in two different categories of spam domains - email spam and mage spam to gain a deeper understanding of this problem.Abstract:
In recent years, online spam has become a major problem for the sustainability of the Internet. Excessive amounts of spam are not only reducing the quality of information available on the Internet but also creating concern amongst search engines and web users. This paper aims to analyse existing works in two different categories of spam domains - email spam and mage spam to gain a deeper understanding of this problem. Future reserch directions are also presented in these spam domains.read more
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Journal ArticleDOI
A survey of emerging approaches to spam filtering
Godwin Caruana,Maozhen Li +1 more
TL;DR: This survey focuses on emerging approaches to spam filtering built on recent developments in computing technologies, which include peer-to-peer computing, grid computing, semantic Web, and social networks.
Journal ArticleDOI
A survey and experimental evaluation of image spam filtering techniques
TL;DR: This paper gives a comprehensive survey and categorisation of computer vision and pattern recognition techniques proposed so far against image spam, and makes an experimental analysis and comparison of some of them on real, publicly available data sets.
Proceedings ArticleDOI
Toward spam 2.0: An evaluation of Web 2.0 anti-spam methods
Pedram Hayati,Vidyasagar Potdar +1 more
TL;DR: Analysis of current anti-spam methods in Web 2.0 for spam detection and prevention against the proposed evaluation framework shows that the need for more robust methods which are prevention based, unsupervised and do not increase user and system interaction complexity is highly demanded.
Journal ArticleDOI
An abusive text detection system based on enhanced abusive and non-abusive word lists
TL;DR: A decision system that successfully detects (obfuscated) abusive text using an unsupervised learning of abusive words based on word2vec's skip-gram and the cosine similarity is designed and integrated into a single system that enhances abusive and non-abusive word lists.
Journal ArticleDOI
A survey of image spamming and filtering techniques
TL;DR: Each image spamming trick is described separately, and by perusing the methods used by researchers to combat them, a classification is drawn in three groups: header-based, content- based, and text-based.
References
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Journal ArticleDOI
A Tutorial on Support Vector Machines for Pattern Recognition
TL;DR: There are several arguments which support the observed high accuracy of SVMs, which are reviewed and numerous examples and proofs of most of the key theorems are given.
Proceedings Article
A Bayesian Approach to Filtering Junk E-Mail
TL;DR: This work examines methods for the automated construction of filters to eliminate such unwanted messages from a user’s mail stream, and shows the efficacy of such filters in a real world usage scenario, arguing that this technology is mature enough for deployment.
Book ChapterDOI
Combating web spam with trustrank
TL;DR: This paper proposes techniques to semi-automatically separate reputable, good pages from spam, and shows that they can effectively filter out spam from a significant fraction of the web, based on a good seed set of less than 200 sites.
Learning to Filter Spam E-Mail: A Comparison of a Naive Bayesian and a Memory-Based Approach
Ion Androutsopoulos,Georgios Paliouras,Vangelis Karkaletsis,Georgios Sakkis,Constantine D. Spyropoulos,Panagiotis Stamatopoulos +5 more
TL;DR: In this article, the authors investigate the performance of two machine learning algorithms in the context of ant-spam filtering and compare them to an alternative memory-based learning approach, after introducing suitable cost-sensitive evaluation measures.