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Ending Spam: Bayesian Content Filtering and the Art of Statistical Language Classification [Paperback]

Jonathan Zdziarski

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Book Description

July 1 2005 1593270526 978-1593270520 1

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


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About the Author

Jonathan Zdziarski is better known as the hacker "NerveGas" in the iPhone development community. His work in cracking the iPhone helped lead the effort to port the first open source applications, and his book, iPhone Open Application Development, taught developers how to write applications for the popular device long before Apple introduced its own SDK. Prior to the release of iPhone Forensics, Jonathan wrote and supported an iPhone forensics manual distributed exclusively to law enforcement. Jonathan frequently consults law enforcement agencies and assists forensic examiners in their investigations. He teaches an iPhone forensics workshop in his spare time to train forensic examiners and corporate security personnel.

Jonathan is also a full-time research scientist specializing in machine learning technology to combat online fraud and spam, an effort that led him to develop networking products capable of learning how to protect customers. He is founder of the DSPAM project, a high-profile, next-generation spam filter that was acquired in 2006 by Sensory Networks, Inc. He lectures widely on the topic of spam and is a foremost researcher in the fields of machine-learning and algorithmic theory.

Jonathan's website is zdziarski.com.


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Front Cover | Copyright | Table of Contents | Excerpt | Index
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Amazon.com: 4.3 out of 5 stars  14 reviews
18 of 20 people found the following review helpful
4.0 out of 5 stars Actually quite entertaining July 16 2005
By Anthony Lawrence - Published on Amazon.com
Format:Paperback
The sub-title of this scared me a bit, because it sounds like heavy geek territory. A review of chapter titles raised my eyebrows a too: "Fifth Order Markovian Discrimination" - I visualized page after page of unintelligible mathematical symbols.

That's not the case at all. Actually Markovian Discrimination is a technique I've used in other programming efforts, and the author explains it in simple and entertaining language. There's nothing here that any competent programmer can't grasp.

I'm a little hesitant to call this book entertaining, although it absolutely is. I only hesitate because that might give the impression that it's more fluff than substance, and that's not the case at all. There's a lot of substance here, both in theory and in practical advice. And although the subject is definitely spam, some of the techniques and methods discussed here apply to other programming challenges as well.

The first part of the book is especially enjoyable. It's a history of spam, and I learned things I hadn't known before about spam's early days. It then segues into analysis; in a sense you get desert before the meat and potatoes.

Overall, worth reading, even by non-programmers wanting to understand more about what current anti-spam efforts are all about.
5 of 5 people found the following review helpful
5.0 out of 5 stars Excellent discussion of spam July 30 2005
By Harold McFarland - Published on Amazon.com
Format:Paperback
Author Jonathan A. Zdziarski starts this book by giving the reader a history of Spam as well as the historical approaches to fighting Spam. This is followed by a very practical guide for the serious Spam fighter; including details on statistical filtering, tokenization, Markovian discrimination, and Bayesian filtering. Although it is very technical in many respects most readers should be able to comprehend the text if they read carefully. Readers who already understand the basics of filtering and email analysis will find it both easy and educational to read.

The author includes an excellent section on spammer tricks and how they get past fileters as well as what to do about it. This section alone makes the book worth the price. Ending Spam is a highly recommended read for anyone in charge of controlling spam in a corporate environment as well as on their own system.
10 of 13 people found the following review helpful
4.0 out of 5 stars Nice overview ... but leaves you wanting more Sept. 18 2005
By Nils Valentin - Published on Amazon.com
Format:Paperback|Verified Purchase
Ending Spam from Mr. Zdziarski is a well written BASIC and easy to understand INTRODUCTION to get a technical overview of todays spam fighting solutions on the market.

Also it is written on the cover that it is f.e focused towards developers, network admins etc. I would consider the target customer to be IT Managers, or other curious people who want to get an overview.

Thats what it does and it does it very well in my eyes.

The book provides simplified, abstract overviews of some available spam filters solutions.

The book is provided into 3 parts

- An Introduction part to spam filtering (Chapter 1-4)

- A part describing "Fundamentals of Statistical Filtering" (Chapter 5-9)

- an the third part describing "Advanced Concepts of Statistical Filtering" (Chapter 10-14)

Its a bit confusing that Chapter 4 has the same title than Part II. So perhaps Chapter 4 should have been part of "Part II" ?

The Chapters which I found most interesting were:

Chapter 4 "Fundamentals of Statistical Filtering"

Chapter 7 "The Low down dirty Tricks of spammers"

Chapter 9 "Scaling in Large Environments"

I am sure the author could have easily filled the book with Chapter 7 alone. The book is very entertaining and has a nice motivating writing style. You might at times find some rant about the spammers which I have chosen to ignore as it doesnt contain any valuable information or anything which I didnt know already. While I might agree to some of the authors views, I believe that the rant does unfortunately do exactly the opposite in my eyes and does give spammers credit to how they do their work.

I personally was actually looking for a companion book to "The Book of Postfix" to help me further explore new anti spam technology.

I was hoping to find overview charts, being able to compare different solutions,features, (dis)advantages. So in this sense, I was actually looking for workshop style instructions, tuning advice, troubleshooting advice etc.

The authors does explain f.e (Chapter 14) Collaborative Algorithms but he does not go into detail which products support the feature and how to perform the setup. He does provide some weblinks in his book from which the interested reader might further investigate the topic.

From reading the Chapter10 on "Testing Theory" its easier to conclude why the author doesnt go into more detail. If he would have done so, the book could have been easily 2-3 times the size.

I assume, this is partly due to the fact that the anti spam technology /products/market is still fairly young .

Summary:

"Ending Spam" gives a very BASIC INTRODUCTION to the current available Anti spam technology and some chosen products. After you have read the book you have a first vague idea what type of solutions exist. You will actually need other books to intensify the "knowledge" you have gained here.

The fact that the book is written in simple terms makes it easily acessable for a wide market, however if you are a technichian you will perhaps find that the book just doesnt contain enough "meat" for you.

I would still recommend the book for Managers which need to know only the rough details, beginners, or a first time read for newcomers.
3 of 3 people found the following review helpful
5.0 out of 5 stars excellent book Jan. 3 2007
By zz l - Published on Amazon.com
Format:Paperback
Reading this book was fun. I was doing some research on spam and found this book was exactly what I was looking for. This book covers (almost) all aspects of spam, including the history, the current status, the principles of anti-spam systems, statistical algorithms, case studies, etc. This book is a good start point for understanding spams and means to stop them, although it does not contain a lot of in-depth technical details. I was amazed by the author's style, which was quite energetic and entertaining. This book made my research a pleasant experience. I strongly recommend this book for those who are interested to know how spams came and how we fight them.
3 of 4 people found the following review helpful
5.0 out of 5 stars Outstanding as a text for applied Bayesian stats June 25 2008
By David L. Bean - Published on Amazon.com
Format:Paperback
This is one of my favorite NLP books because it offers an extremely readable introduction to Bayesian statistics in a very applied context. If you don't have a strong background in statistics and/or text classification, this book is a great way to get an intuitive feel for how Bayesian classifiers work. If you're a developer looking to do some coding, what's explained in the book is easy to translate into code. I recommend this book to upper-level undergrads and graduate students in linguistics who take an applied computational linguistic class I teach.

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