TY  - BOOK
AU  - Lee,Wenke
AU  - Wang,Cliff
AU  - Dagon,David
ED  - SpringerLink (Online service)
TI  - Botnet Detection: Countering the Largest Security Threat 
T2  - Advances in Information Security,
SN  - 9780387687681
AV  - QA76.9.A25 
U1  - 005.8 23
PY  - 2008///
CY  - Boston, MA
PB  - Springer US
KW  - Computer science
KW  - Computer network architectures
KW  - Computer Communication Networks
KW  - Data protection
KW  - Data structures (Computer science)
KW  - Data encryption (Computer science)
KW  - Information systems
KW  - Computer Science
KW  - Systems and Data Security
KW  - Data Encryption
KW  - Information Systems Applications (incl.Internet)
KW  - Data Structures, Cryptology and Information Theory
KW  - Computer Systems Organization and Communication Networks
N1  - 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
N2  - 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.
UR  - http://dx.doi.org/10.1007/978-0-387-68768-1
ER  -