Ending Spam

Informationen zum Autor 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. Klappentext Join author Jonathan 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 filtersAfter 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 curios 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. Zusammenfassung Join author Jonathan 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 filtersAfter 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 curios 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. Inhaltsverzeichnis 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

• Authors: Jonathan Zdziarski, Jonathan A. Zdziarski
• Publisher: No Starch Press
• Languages: English
• Product format: Paperback / Softback
• Released: 01.01.2005
• EAN: 9781593270520
• ISBN: 978-1-59327-052-0
• No. of pages: 312
• Subjects: Guides > Self-help, everyday life > Practical guides; Natural sciences, medicine, IT, technology > IT, data processing > Data communication, networks; E-Mail