–While email is one of the fastest form of communication, the user is frequently faced with receiving unsolicited emails called spams. Nonspam mails are known as hams which are legitimate mails. It is practically very difficult to perfectly classify a mail into spam or ham basing on the content or subject of the mail. Several statistical methods are available which classify mails with some chan...

Spam is no more garbage but risk as it includes virus attachments and spyware agents which make the recipients’ system ruined, therefore, there is an emerging need for spam detection. Many spam detection techniques based on machine learning algorithms have been proposed. As the amount of spam has been increased tremendously using bulk mailing tools, spam detection techniques should deal with it...

Unsolicited bulk email (aka. spam) is a major problem on the Internet. To counter spam, several techniques, ranging from spam filters to mail protocol extensions like hashcash, have been proposed. In this paper we investigate the effectiveness of several spam filtering techniques and technologies. Our analysis was performed by simulating email traffic under different conditions. We show that ge...

Unsolicited bulk email (aka. spam) is a major problem on the Internet. To counter spam, several techniques, ranging from spam filters to mail protocol extensions like hashcash, have been proposed. In this paper we investigate the effectiveness of several spam filtering techniques and technologies. Our analysis was performed by simulating email traffic under different conditions. We show that ge...

The Subspace Precision and Mean model (SPAM) is a way of representing Gaussian precision and mean values in a reduced dimension. This paper presents some large vocabulary experiments with SPAM and introduces an efficient way to optimize the SPAM basis. We present experiments comparing SPAM, diagonal covariance and full covariance models on a large vocabulary task. We also give explicit formulae...

OBJECTIVE The objective of this study was to determine whether administration of the situation present assessment method (SPAM) affects workload and/or task performance. BACKGROUND SPAM probes are thought to isolate workload from the assessment of situation awareness (SA) by including a warning signal before asking an SA-related question. However, there is a good reason to think that SPAM may...

Current studies on spam evolution usually extract evolution patterns and trends by analyzing historical spam message corpora. In this paper, we propose a novel methodology that incorporates spam filters to the spam trend analysis, as they are the agents that may force spammers to change their tactics. Moreover, filters also evolve over time and different filter releases present different charac...

Web spam detection is an important problem in Web search. Since Web spam pages tend to have a lot of spurious links, many Web spam detection algorithms exploit the hyperlink structure between the Web pages to detect the spam pages. Anti-TrustRank algorithm is a well-known link-based spam detection algorithm which follows the principle that spam pages are likely to be referenced by other spam pa...

The fight to curb the ever-increasing amount of unsolicited commercial email or “spam” showing up in the inboxes of American businesses has generated both state and federal legislation. The CAN-SPAM Act of 2003 was enacted to create a bright-line between spam and legal commercial email. The Act preempted many state spam laws but also left significant enforcement abilities to the individual stat...