In this paper, we document our efforts in participating to the TREC 2010 Entity Ranking and Web Tracks. We had multiple aims: For the Web Track we wanted to compare the effectiveness of anchor text of the category A and B collections and the impact of global document quality measures such as PageRank and spam scores. For the Entity Ranking Track, we use Wikipedia as a pivot to find relevant ent...

Unsolicited commercial email is a significant problem for users and providers of email services. While statistical spam filters have proven useful, senders of spam are learning to bypass these filters by systematically modifying their email messages. In a good word attack, one of the most common techniques, a spammer modifies a spam message by inserting or appending words indicative of legitima...

Unsolicited commercial email, commonly referred to as spam, is now recognized as a major problem causing considerable costs (e.g., [Ferris Research 03]) and impacting on how people use email (e.g., [Fallows 03]). Anti-spam measures, such as email filters and server-based block lists, have become ubiquitous. There is a growing body of empirical and anecdotal evidence suggesting that apart from t...

Data from two nationwide surveys suggest that spam is beginning to undermine the integrity of email and even to discourage its use. The vast majority of Internet users are outspoken in their disdain for spam, although enough of them respond to commercial offers that spam remains a viable source of income to spammers. While most users want to do the right thing to avoid and get rid of spam, they...

Due to the constant increase in the volume of information available to applications in fields varying from medical diagnosis to web search engines, accurate support of similarity becomes an important task. This is also the case of spam filtering techniques where the similarities between the known and incoming messages are the fundaments of making the spam/not spam decision. We present a novel a...

We propose a variant of the k-nearest neighbor classification method, called instance-weighted k-nearest neighbor method, for adaptive spam filtering. The method assigns two weights, distance weight and correctness weight, to a training instance, and makes use of the two weights when classifying a new email. The correctness weight is also used in the maintenance of the training data to make the...

This paper proposes a multimodal framework that clusters spam images so that ones from the same spam source/cluster are grouped together. By identifying the common sources of spam images, we can provide evidence in tracking spam gangs. For this purpose, text recognition and visual feature extraction are performed. Subsequently, a two-level clustering method is applied where images with visually...

Blogs are becoming an increasingly popular target for spammers. The existence of multiple vectors for spam injection, the potential of reaching many eyeballs with a single spam, and limited deployment of anti-spam technologies has led to a sustained increase in the volume and sophistication of attacks. This paper reviews the current state of spam in the blogosphere at large and in particular as...

Stock spam is a part of unsolicited electronic mail which wants its receiver to buy a certain share at the stock markets. As there is no direct profit for the sender of this message, impacts on the share prices seem to be the only way to generate earnings by the spam sender. To hide the information within stock spam messages from automatic processing, textual and image-based distortions are use...

In this paper we present Botlab, a platform that continually monitors and analyzes the behavior of spamoriented botnets. Botlab gathers multiple real-time streams of information about botnets taken from distinct perspectives. By combining and analyzing these streams, Botlab can produce accurate, timely, and comprehensive data about spam botnet behavior. Our prototype system integrates informati...