DocumentCode
621185
Title
Detecting encrypted botnet traffic
Author
Han Zhang ; Papadopoulos, Christos ; Massey, Dan
Author_Institution
Comput. Sci. Dept., Colorado State Univ., Fort Collins, CO, USA
fYear
2013
fDate
14-19 April 2013
Firstpage
163
Lastpage
168
Abstract
Bot detection methods that rely on deep packet inspection (DPI) can be foiled by encryption. Encryption, however, increases entropy. This paper investigates whether adding high-entropy detectors to an existing bot detection tool that uses DPI can restore some of the bot visibility. We present two high-entropy classifiers, and use one of them to enhance BotHunter. Our results show that while BotHunter misses about 50% of the bots when they employ encryption, our high-entropy classifier restores most of its ability to detect bots, even when they use encryption.
Keywords
computer network security; cryptography; entropy; inspection; peer-to-peer computing; telecommunication traffic; BotHunter enhancement; DPI; advanced hybrid peer-to-peer botnet; bot detection methods; bot detection tool; deep packet inspection; encrypted botnet traffic detection; high-entropy classifiers; high-entropy detectors; Detectors; Encryption; Entropy; IP networks; Malware; Payloads;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Communications Workshops (INFOCOM WKSHPS), 2013 IEEE Conference on
Conference_Location
Turin
Print_ISBN
978-1-4799-0055-8
Type
conf
DOI
10.1109/INFCOMW.2013.6562912
Filename
6562912
Link To Document