Stopping SPAM

In the April 2005 issue of Scientific American, read an in-depth feature on what can be done to staunch the flood of SPAM email messages and the future of anti-spam technology.

New York, NY (PRWEB) March 28, 2005 -- SPAM or junk e-mail constitutes over two-thirds of all e-mail transmitted over the Internet which make up billions of e-mail messages every day. For a third of all e-mail users, 80% of the messages received are spam." On March 28, read an in-depth article on the techniques spammers use to flood your inbox with junk e-mail and the latest methods being developed to stop them. (The article can be found for free on the Scientific American web site -- www.sciam.com/features)

With the advent of the Internet and e-mail, spam has grown to become a suffocating problem. The relatively cheap cost of e-mail, which is estimated at one-hundredth of a cent to send, has led to the proliferation of fraudulent junk e-mail and threatens the security of Internet communications. The authors, Goodman, Heckerman and Roundthwaite, have been working on defeating spammers since 1997 and are continuing the war against spam today. The three authors provide an in-depth look into how spammers defeat current anti-spam methods such as fingerprint matching" utilizing clever but simple techniques while anti-spammers develop new e-mail filtering methods using advanced algorithms. The authors also explore how new techniques called proof tests or human intervention proofs (HIP) can be used in combination with filter technology to form an effective combination against spammers as well as the need for multi-pronged attack against spammers which include legislation, changes in Internet standards, email technology and supporting services.

With the increasing persistence of spammers and the financial impact junk e-mail, reducing spam has become a priority. The introduction of new technology and techniques in combination with current methods as well as legislation may someday completely eliminate spam or hopefully slow the flood to a trickle.

To read this article visit www.sciam.com/features
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About the Authors
Joshua Goodman, David Heckerman and Robert Rounthwaite have worked together on ways to stop spam for many years. Heckerman and Rounthwaite, with others, created the fi rst machine-learning spam filter in 1997. Heckerman manages the Machine Learning and Applied Statistics (MLAS) group at Microsoft Research. Goodman and Rounthwaite helped to organize the Microsoft product team that delivers the anti-spam technologies deployed in Exchange, Outlook, MSN and Hotmail. Rounthwaite is currently the groups chief architect. Goodman is a member of the MLAS team and does research on spam and e-mail-related topics.

Contact Information:
Han Ko
Scientific American
Tel: 212-451-8524
Fax: 212-832-2998
Email: hko@sciam.com

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