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...

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...

Embedded-Text Detection and Its Application to Anti-Spam Filtering Ching-Tung Wu Embedded-text in images usually carry important messages about the content. In the past, several algorithms have been proposed to detect text boxes in video frames. Previous work often followed a multi-step framework using a combination of image-analysis and machine-learning techniques. In this work, we propose a u...

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...

In order to protect email users from receiving unsolicited commercial email or spam, anti-spam measures building on technologies, such as filters and block lists, have been deployed widely. However, there is some evidence that certain antispam measures based on the purported origin of the spam cause unintended consequences related to issues of equity of access, which we term digital redlining. ...

Spam as unsolicited e-mail has certainly crossed the border of just being bothersome. In 2003, it surpassed legitimate e-mail – growing to more than 50% of all Internet e-mails. Annually, it causes economic harms of several billion Euros. Fighting spam, beside legal approaches especially technical means are deployed in practical systems, mainly focussing on blocking and filtering mechanisms. Th...

Unsolicited bulk email (spam) is used by cybercriminals to lure users into scams and to spread malware infections. Most of these unwanted messages are sent by spam botnets, which are networks of compromised machines under the control of a single (malicious) entity. Often, these botnets are rented out to particular groups to carry out spam campaigns, in which similar mail messages are sent to a ...