Ending Spam: Bayesian Content Filtering and the Art of Statistical Language Classification - Softcover

Zdziarski, Jonathan

3.7

30 ratings by Goodreads

9781593270520: Ending Spam: Bayesian Content Filtering and the Art of Statistical Language Classification

Softcover

ISBN 10: 1593270526 ISBN 13: 9781593270520

Publisher: No Starch Press, 2005

View all copies of this ISBN edition:

Join author John Zdziarski for a look inside the brilliant minds that have conceived clever new ways to fight spam in all its nefarious forms. This landmark title describes, in-depth, how statistical filtering is being used by next-generation spam filters to identify and filter unwanted messages, how spam filtering works and how language classification and machine learning combine to produce remarkably accurate spam filters.

After reading Ending Spam, you'll have a complete understanding of the mathematical approaches used by today's spam filters as well as decoding, tokenization, various algorithms (including Bayesian analysis and Markovian discrimination) and the benefits of using open-source solutions to end spam. Zdziarski interviewed creators of many of the best spam filters and has included their insights in this revealing examination of the anti-spam crusade.

If you're a programmer designing a new spam filter, a network admin implementing a spam-filtering solution, or just someone who's curious about how spam filters work and the tactics spammers use to evade them, Ending Spam will serve as an informative analysis of the war against spammers.

TOCIntroduction

PART I: An Introduction to Spam FilteringChapter 1: The History of SpamChapter 2: Historical Approaches to Fighting SpamChapter 3: Language Classification ConceptsChapter 4: Statistical Filtering Fundamentals

PART II: Fundamentals of Statistical FilteringChapter 5: Decoding: Uncombobulating MessagesChapter 6: Tokenization: The Building Blocks of SpamChapter 7: The Low-Down Dirty Tricks of SpammersChapter 8: Data Storage for a Zillion RecordsChapter 9: Scaling in Large Environments

PART III: Advanced Concepts of Statistical FilteringChapter 10: Testing TheoryChapter 11: Concept Identification: Advanced TokenizationChapter 12: Fifth-Order Markovian DiscriminationChapter 13: Intelligent Feature Set ReductionChapter 14: Collaborative Algorithms

Appendix: Shining Examples of Filtering

Index

"synopsis" may belong to another edition of this title.

About the Author:

Jonathan A. Zdziarski has been fighting spam for eight years, and has spent a significant portion of the past two years working on the next generation spam filter DSPAM, with up to 99.985% accuracy. Zdziarski lectures widely on the topic of spam.

Review:

A highly recommended read for anyone in charge of controlling spam in a corporate environment. -- Midwest Book Review, September 2005 (http://www.midwestbookreview.com/mbw/sep_05.htm)

Does a good job of addressing advanced, complicated issues, but putting it in terms that readers can grasp. -- Netsecurity.about.com, August 29, 2005, http://netsecurity.about.com/od/5/fr/aabrendspam.htm

Does a great job educating us on logic and thought taken to combat this SPAM blight on the Internet. -- MacCompanion, August 2005, 5 out of 5 stars

Highly recommended read for anyone in charge of controlling spam in a corporate environment [and] on their own system. -- Readers Preference, readerspreference.com/reviews/endingspam.html

IT managers who want a better understanding of how anti-spam products work should shell out the $39.95 price at once. -- eWeek, July 25, 2005

If you’re looking for a primer on how the anti-spam battle is fought, you can’t do much better. -- InfoWorld, July 14, 2005,

Leads the charge against what has become a very significant challenge to both productivity and sanity -- Book News, September 2005 (http://www.booknews.com/issues/sci-current.pdf)

Not only enjoyable but actually captivating. -- Linux Magazine, October 2005 (http://www.linux-magazine.com/issue/59/Book_Reviews.pdf)

The first book explaining the fine details of the theoretical models and machine-learning algorithms implemented in these filters. -- Slashdot, August 15, 2005

This book is down, and dirty, loaded with information, and will make your head-hurt (in a good way). -- MyMac, August 29, 2005, mymac.com/showarticle.php?id=2074

"About this title" may belong to another edition of this title.