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...

In this work we are concerned in use semantic concepts to filter spam videos on video sharing social networks. Specifically, we investigate how much semantic-based information analysis, based on content-based visual information retrieval (CBVIR), can aid in detecting spam videos. This is a very challenging task, because of the high-level semantic concepts involved; of the assorted nature of soc...

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...

Over recent years, as the popularity of mobile phone devices has increased, Short Message Service (SMS) has grown into a multi-billion dollars industry. At the same time, reduction in the cost of messaging services has resulted in growth in unsolicited commercial advertisements (spams) being sent to mobile phones. In parts of Asia, up to 30% of text messages were spam in 2012. Lack of real data...

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 ...