A substantial majority of the email sent everyday is spam. Spam emails cause many problems if someone acts or clicks on the link provided in the email body. The problems may include infecting users personal machine with malware, stealing personal information, capturing credit card information, etc. Since spam emails are generated as a part of a very limited numbers of spam campaigns, it is usef...

Recently, email has become a common way for people to communicate and share information both officially personally. Email may be used by spammers transmit harmful materials Internet users. The data must protected from unauthorized access, which necessitates the development of reliable method identifying spam emails. As result, variety solutions have been devised. An innovative hybrid machine le...

Today the major problem that the people are facing is spam mails or e-mail spam. In recent years there are so many schemes are developed to detect the spam emails. Here the primary idea of the similarity matching scheme for spam detection is to maintain a known spam database, formed by user’s feedback, to block the subsequent near-duplicate spam’s. We propose a novel e-mail abstraction scheme, ...

This article presents an extensive characterization of a spam-infected e-mail workload. The study aims at identifying and quantifying the characteristics that significantly distinguish spam from non-spam (i.e., legitimate) traffic, assessing the impact of spam on the aggregate traffic, providing data for creating synthetic workload models, and drawing insights into more effective spam detection...

User feedback is vital to the quality of the collaborative spam fi lters frequently used in open membership email systems such as Yahoo Mail or Gmail. Users occasionally designate emails as spam or non-spam (often termed as ham), and these labels are subsequently used to train the spam fi lter. Although the majority of users provide very little data, as a collective the amount of training data ...

Statistical spam filters are known to be vulnerable to adversarial attacks. One of the more common adversarial attacks, known as the good word attack, thwarts spam filters by appending to spam messages sets of “good” words, which are words that are common in legitimate email but rare in spam. We present a counterattack strategy that attempts to differentiate spam from legitimate email in the in...

Spam is pervasive across many types of electronic communication, including email, instant messaging, and social networks. To reach more users and increase financial gain, many spammers now use multiple content-sharing platforms— including online social networks—to disseminate spam. In this paper, we perform a joint analysis of spam in email and social networks. We use spam data from Yahoo’s web...

Spam pages are designed to maliciously appear among the top search results by excessive usage of popular terms. Therefore, spam pages should be removed using an effective and efficient spam detection system. Previous methods for web spam classification used several features from various information sources (page contents, web graph, access logs, etc.) to detect web spam. In this paper, we follo...

The presence of spam in a document ranking is a major issue for Web search engines. Common approaches that cope with spam remove from the document rankings those pages that are likely to contain spam. These approaches are implemented as post-retrieval processes, that filter out spam pages only after documents have been retrieved with respect to a user’s query. In this paper we propose removing ...

Abstract Spam annoys users and poses a security threat. This article proposes spam filter based on geographical location of the sender determined by IP geolocation. was implemented as plugin to SpamAssassin anti-spam software. The allows define penalty score for specific countries sending spam. proposed tested dataset 1500 e-mails consisting 1200 300 legitimate e-mails. Matthews correlation coe...