In today’s world of globalization and borderless technology, the explosion in communication has revolutionized the field of electronic communication. The e-mail is therefore one of the most used methods for its efficiency and profitability. In the last few years, the undesirables emails (SPAM) are widely spread as they play an important part in the inbox. so that such emails must be filtered an...

Phishing is the use of fraudulent emails to obtain personal financial information from victims by posing as legitimate financial institutions or commerce sites. This exploratory study involved interviewing 104 participants, 50 of whom reported having received a phishing email. The theoretical foundation for this research is Routine Activity Theory, whereby crime is considered to be the conseque...

Viagra is a popular topic in spam, but contrary to Pfizer's official marketing of Viagra, little attention has been directed at how the content spam plays into gendered discourse on masculinity and men's sexual performances. This not surprising, if we consider mostly treated as nuisance digital infrastructures. Yet, studies have demonstrated spammers build on, reflect transmit gender ideologies...

The judgment that whether an email is spam or non-spam may vary from person to person. Different individuals can have totally different responses to the same email based on their preferences. This paper presents an innovative approach that incorporates user preferences to construct an anti-spam mail system, which is different from the conventional content-based approaches. We build a user prefe...

In this paper a spam filtering method is proposed. We focus on user behavior that most email users browse the Web. The method reduces troublesome maintenance of the spam filter, since the filter learns from Web browsing behavior in the background. The method uses Web browsing behavior of each user to learn ham words. Ham words are picked up from browsed Web pages using TF-IDF and stored in the ...

In this paper, we propose a novel feature selection method— INTERACT to select relevant words of emails for spam email filtering, i.e. classifying an email as spam or legitimate. Four traditional feature selection methods in text categorization domain, Information Gain, Gain Ratio, Chi Squared, and ReliefF, are also used for performance comparison. Three classifiers, Support Vector Machine (SVM...

Economic lifting has made email spam a scathing threat to the society due to its related exploits. Many spam detection schemes have been proposed employing the tendency of spam to alter the normal statistical behavior of mail traffic. Threshold tuning of these detectors is still a challenging task. Since, shooting down benign emails as spam (false positive), in pursuit of higher detection rates...

Early spam mails were only text-based, however spammers have moved to more sophisticated spamming techniques that involve images now generally termed image based spam. In most image-based spam, the entire spam message, which could be sometimes text, is embedded in an image of any format. This type of spam emails creates another dimension to the spam filtering problem scenario. Extracting text f...

With the generalization of mobile communication systems, solicitations of all kinds in the form of messages and emails are received by users with increasing proportion of malicious ones. They are customized to pass anti-spam filters and ask the person to click or to open the joined dangerous attachment. Current filters are very inefficient against spear phishing emails. It is proposed to improv...

Image spam is a new trend in the family of email spams. The new image spams employ a variety of image processing technologies to create random noises. In this paper, we propose a semi-supervised approach, regularized discriminant EM algorithm (RDEM), to detect image spam emails, which leverages small amount of labeled data and large amount of unlabeled data for identifying spams and training a ...