Unsolicited Bulk Emails (also known as Spam) are undesirable emails sent to massive number of users. Spam emails consume the network resources and cause lots of security uncertainties. As we studied, the location where the spam filter operates in is an important parameter to preserve network resources. Although there are many different methods to block spam emails, most of program developers on...

An efficient anti-spam filter that would block all unsolicited messages i.e. spam, without blocking any legitimate messages is a growing need. To address this problem, this report takes a statistically-based approach, employing a Bayesian anti-spam filter, because it is content-based and self-learning (adaptive) in nature. We train the filter, using a large corpus of legitimate messages and spa...

Spam web pages intend to achieve higher-than-deserved ranking by various techniques. While human experts could easily identify spam web pages, the manual evaluating process of a large number of pages is still time consuming and cost consuming. To assist manual evaluation, we propose an algorithm to assign spam values to web pages and semi-automatically select potential spam web pages. We first ...

BadRank is a method for detecting spam web sites, based on the premise that a page is spam if it points to another spam page; i.e., the BadRank score of a page is the weighted sum of the BadRank scores of the pages that it links to. BadRank is an important tool in spam detection. We consider the mathematical structure of BadRank, showing how it can be modified to guarantee that the iterates con...

Web Spam is the result of a number of methods to deceive search engine algorithms so as to obtain higher ranks in the search results. Advanced spammers use keyword and link stuffing methods to create farms of spam pages. Most of the recent works in the web spam detection literature utilize graph based methods to enhance the accuracy of this task. This paper is basically a probabilistic approach...

Unsolicited email campaigns remain as one of the biggest threats affecting millions of users per day. Spam filters are capable of detecting and avoiding an increasing number of messages, but researchers have quantified a response rate of a 0.006% [1], still significant to turn a considerable profit. While research directions are addressing topics such as better spam filters, or spam detection i...

Spam content is surging with an explosive increase of user generated content (UGC) on the Internet. Spammers often insert popular keywords or simply copy and paste recent articles from the Web with spam links inserted, attempting to disable content-based detection. In order to effectively detect spam in user generated content, we first conduct a comprehensive analysis of spamming activities on ...

Over the last decade, unsolicited bulk email—spam— has evolved dramatically in its volume, its delivery infrastructure and its content. Multiple reports indicate that more than 90% of all email traversing the Internet today is considered spam. This growth is partially driven by a multi-billion dollar anti-spam industry whose dedication to filtering spam in turn requires spammers to recruit botn...

Spam is a major threat to web security. The web of trust is being abused by the spammers through their ever evolving new tactics for their personal gains. In fact, there is a long chain of spammers who are running huge business campaigns under the web. Spam causes underutilization of search engine resources and creates dissatisfaction among web community. Web Security being a prime challenge fo...

The web spam detection problem was considered in the paper. Based on interconnected spam and no-spam hosts a collective classification approach based on label propagation is aimed at discovering the spam hosts. Each host is represented as network node and links between hosts constitute network’s edges. The proposed method provides reasonable results and is able to compute large data as is settl...