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.
Edited by:
Wenke Lee, Cliff Wang, David Dagon Imprint: Springer-Verlag New York Inc. Country of Publication: United States Volume: 36 Dimensions:
Height: 235mm,
Width: 155mm,
Spine: 12mm
Weight: 970g ISBN:9780387687667 ISBN 10: 0387687661 Series:Advances in Information Security Pages: 168 Publication Date:29 November 2007 Audience:
Professional and scholarly
,
Undergraduate
Format:Hardback Publisher's Status: Active
Botnet Detection Based on Network Behavior.- Honeynet-based Botnet Scan Traffic Analysis.- Characterizing Bots’ Remote Control Behavior.- Automatically Identifying Trigger-based Behavior in Malware.- Towards Sound Detection of Virtual Machines.- Botnets and Proactive System Defense.- Detecting Botnet Membership with DNSBL Counterintelligence.- A Taxonomy of Botnet Structures.