Botnet Detection: Countering the Largest Security Threat

Lee, Wenke (Editor) / Wang, Cliff (Editor) / Dagon, David (Editor)

ISBN 10: 1441943307 / ISBN 13: 9781441943309

Published by Springer US, 2007

About this Item

180 pages. 8.90x5.98x0.55 inches. In Stock.

Seller Inventory # x-1441943307

Bibliographic Details

• Title: Botnet Detection: Countering the Largest Security Threat
• Publisher: Springer US
• Publication Date: 2007
• Language: English
• ISBN 10: 1441943307
• ISBN 13: 9781441943309
• Binding: Paperback
• Condition: Brand New

About this title

Synopsis

Botnets have become the platform of choice for launching attacks and committing fraud on the Internet. A better understanding of Botnets will help to coordinate and develop new technologies to counter this serious security threat. Botnet Detection: Countering the Largest Security Threat consists of chapters contributed by world-class leaders in this field, from the June 2006 ARO workshop on Botnets. This edited volume represents the state-of-the-art in research on Botnets. It is intended for researchers and advanced-level students in computer science. This book is also appropriate for practitioners in industry.

From the Back Cover

Botnets have become the platform of choice for launching attacks and committing fraud on the Internet. A better understanding of Botnets will help to coordinate and develop new technologies to counter this serious security threat.

Botnet Detection: Countering the Largest Security Threat, a contributed volume by world-class leaders in this field, is based on the June 2006 ARO workshop on Botnets. This edited volume represents the state-of-the-art in research on Botnets. It provides botnet detection techniques and response strategies, as well as the latest results from leading academic, industry and government researchers.

Botnet Detection: Countering the Largest Security Threat is intended for researchers and practitioners in industry. This book is also appropriate as a secondary text or reference book for advanced-level students in computer science.