Spam is an unwanted email that is harmful to communications around the world. Spam leads to a growing problem in a personal email, so it would be essential to detect it. Machine learning is very useful to solve this problem as it shows good results in order to learn all the requisite patterns for classification due to its adaptive existence. Nonetheless, in spam detection, there are a large num...

Twitter is one of the most visited sites in these days. Twitter spam, however, is constantly increasing. Since Twitter spam is different from traditional spam such as email and blog spam, conventional spam filtering methods are inappropriate to detect it. Thus, many researchers have proposed schemes to detect spammers in Twitter. These schemes are based on the features of spam accounts such as ...

The Cost Impact of Spam Filters: Measuring the Effect of Information System Technologies in Organizations More than 70% of global e-mail traffic consists of unsolicited and commercial direct marketing, also known as spam. Dealing with spam incurs high costs for organizations, prompting efforts to try to reduce spam-related costs by installing spam filters. Using modern econometric methods to re...

Search engines have tried many techniques to filter out these spam pages before they can appear on the query results page. In Section 2 we present a collection of current methods that are being used to combat spam. We introduce a new approach to spam detection in Section 3 that uses semantic analysis of textual content as a means of detecting spam. This new approach uses a series of content ana...

This dissertation discusses techniques to improve the effectiveness and the efficiency of spam control. Specifically, layer-3 e-mail content classification is proposed to allow e-mail pre-classification (for fast spam detection at receiving e-mail servers) and to allow distributed processing at network nodes for fast spam detection at spam control points, e.g., at e-mail servers. Fast spam dete...

Spam messages are capable of carrying links to disconnected portions of the Internet. This paper looks the web as it is visible through URLs embedded in spam. We perform a study of spam using three sources: a spam honeypot, a group of high-spam student inboxes and a newsgroup devoted to posting spam messages. Our results show that 96% of spam links point to sites not reacheable by crawlers and ...

Spam is information crafted to be delivered to a large number of recipients, in spite of their wishes. A spam filter is an automated tool to recognize spam so as to prevent its delivery. The purposes of spam and spam filters are diametrically opposed: spam is effective if it evades filters, while a filter is effective if it recognizes spam. The circular nature of these definitions, along with t...

Identifying and detecting web spam is an ongoing battle between spam-researchers and spammers which has been going on since search engines allowed searching of web pages to the modern sharing of web links via social networks. A common challenge faced by spam-researchers is the fact that new techniques depend on requiring a corpus of legitimate and spam web pages. Although large corpora of legit...