Spam has emerged as a major problem in recent years. The most widely recognized form of spam, is email spam. The accounts which contain spam messages must waste time deleting annoying and possibly offensive message. In this paper, we present a variety of machine learning algorithms to identify spam in e-mail accounts. We design classifier model to automatically determine spam in the accounts so...

Unsolicited email (spam) is still a problem for users of the email service. Even though current email anti-spam solutions filter most spam emails, some still are delivered to the inbox of users. A special class of spam emails advertises websites, e.g., online dating sites or online pharmacies. The success rate of this kind of advertising is rather low, however, as sending an email does only inv...

Email is an increasingly important and ubiquitous mean of communication, both facilitating contact between individuals and enabling rises in the productivity of organizations. However, the relentless rising of automatic unauthorized emails, also known as spam, is eroding away much of the attractiveness of email communication. Most of the attention dedicated to spam detection has focused on the ...

In this paper, using a year (June 2011 to May 2012) of user reported SMS spam messages together with SMS network records collected from a large US based cellular carrier, we carry out a comprehensive study of SMS spamming. Our analysis shows various characteristics of SMS spamming activities, such as spamming rates, victim selection strategies and spatial clustering of spam numbers. Our analysi...

The main challenge of mining sequential patterns is the high processing cost of support counting for large amount of candidate patterns. For solving this problem, SPAM algorithm was proposed in SIGKDD’2002, which utilized a depth-first traversal on the search space combined with a vertical bitmap representation to provide efficient support counting. According to its experimental results, SPAM o...

This paper proposes a mutual detection mechanism between spam blogs and words with bipartite graph clustering for fi ltering spam blogs from updated blog data. Spam blogs are problematic in extracting useful marketing information from the blogosphere; they often appear to be rich sources of information based on individual opinion and social reputation. One characteristic of spam blogs is copied...

Currently, spam and scams are passive attack over the inbox which can initiated to steal some confidential information, to spread Worms, Viruses, Trojans, cookies and Sometimes they are used for phishing attacks. Spam mails are the major issue over mail boxes as well as over the internet. Spam mails can be the cause of phishing attack, hacking of banking accounts, attacks on confidential data. ...

Spam, also known as Unsolicited Commercial Email (UCE), has been an increasingly annoying problem to individuals and organizations. Most of prior research formulated spam filtering as a classical text categorization task, in which training examples must include both spam emails (positive examples) and legitimate mails (negatives). However, in many spam filtering scenarios, obtaining legitimate ...

The A theory of user expectation of system interaction is introduced in the context of User Adapted Interfaces. The usability of an intelligent email client that learns to filter spam emails is tested under three variants of adaptation: no user modeling, user modeling with fixed (optimal) spam cut-offs, and user modeling with user adjustable spam cut-offs. The results supported our hypothesis t...