Ending Spam [Minkštas viršelis]

Explains how spam works, how network administrators can implement spam filters, or how programmers can develop new remarkably accurate filters using language classification and machine learning. Original. (Advanced) Zdziarski, who maintains a spam filter that can achieve a level of accuracy up to 99.985 percent, leads the charge against what has become a very significant challenge to both productivity and sanity by explaining how it was spawned, its anatomy and physiognomy, how it crawled into our pristine PCs, and how, as responsible and gleeful citizens, we can torch it. He covers how early spam wars were fought and the lessons learned, language classification concepts and statistical filtering fundamentals, and advanced concepts such as testing theory, concept identification, Markovian discrimination, intelligent feature set reductions, and collaborative algorithms. The final chapter includes what Zdziarski terms shining examples of filtering. Annotation ©2005 Book News, Inc., Portland, OR (booknews.com) Fascinating reading for any geek, this landmark title describes, in-depth, how statistical filtering is being used by next generation spam filters to identify and filter spam. 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, youll have a complete understanding of the mathematical approaches used by todays 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 youre a programmer designing a new spam filter, a network admin implementing a spam-filtering solution, or just someone whos 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 RecordsChapter 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