 | Ending Spam: Bayesian Content Filtering and the Art of Statistical Language Classification |
| List Price: | $39.95 |
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Product Description
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.
TOC Introduction
PART I: An Introduction to Spam Filtering Chapter 1: The History of Spam Chapter 2: Historical Approaches to Fighting Spam Chapter 3: Language Classification Concepts Chapter 4: Statistical Filtering Fundamentals
PART II: Fundamentals of Statistical Filtering Chapter 5: Decoding: Uncombobulating Messages Chapter 6: Tokenization: The Building Blocks of Spam Chapter 7: The Low-Down Dirty Tricks of Spammers Chapter 8: Data Storage for a Zillion Records Chapter 9: Scaling in Large Environments
PART III: Advanced Concepts of Statistical Filtering Chapter 10: Testing Theory Chapter 11: Concept Identification: Advanced Tokenization Chapter 12: Fifth-Order Markovian Discrimination Chapter 13: Intelligent Feature Set Reduction Chapter 14: Collaborative Algorithms
Appendix: Shining Examples of Filtering
Index
Product Details
- Amazon Sales Rank: #849171 in Books
- Published on: 2005-07-01
- Released on: 2005-07-01
- Original language: English
- Number of items: 1
- Dimensions: .72" h x 7.00" w x 9.24" l, 1.12 pounds
- Binding: Paperback
- 312 pages
Features
- ISBN13: 9781593270520
- Condition: New
- Notes: BRAND NEW FROM PUBLISHER! 100% Satisfaction Guarantee. Tracking provided on most orders. Buy with Confidence! Millions of books sold!
Editorial Reviews
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 the Author
Jonathan Zdziarski is better known as the hacker "NerveGas" in the iOS development community. His work in cracking the iPhone helped lead the effort to port the first open source applications to it, and his book iPhone Open Application Development taught developers how to write applications for the popular device long before Apple introduced its own SDK. Jonathan is also the author of many other books, including iPhone SDK Application Development and iPhone Forensics. Jonathan presently supports over 2,000 law enforcement agencies worldwide and distributes a suite of iOS forensic imaging tools to obtain evidence from iOS devices for criminal cases. He frequently consults and trains law enforcement agencies and assists forensic examiners in their investigations.
Jonathan is also a full-time Sr. Forensic Scientist, where, among other things, he performs penetration testing of iOS applications for corporate clients.
