A collaborative approach to botnet protection

Publication: Research - peer-reviewArticle in proceedings – Annual report year: 2012

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Botnets are collections of compromised computers which have come under the control of a malicious person or organisation via malicious software stored on the computers, and which can then be used to interfere with, misuse, or deny access to a wide range of Internet-based services. With the current trend towards increasing use of the Internet to support activities related to banking, commerce, healthcare and public administration, it is vital to be able to detect and neutralise botnets, so that these activities can continue unhindered. In this paper we present an overview of existing botnet detection techniques and argue why a new, composite detection approach is needed to provide efficient and effective neutralisation of botnets. This approach should combine existing detection efforts into a collaborative botnet protection framework that receives input from a range of different sources, such as packet sniffers, on-access anti-virus software and behavioural analysis of network traffic, computer sub-systems and application programs. Finally, we introduce ContraBot, a collaborative botnet detection framework which combines approaches that analyse network traffic to identify patterns of botnet activity with approaches that analyse software to detect items which are capable of behaving maliciously. © 2012 IFIP International Federation for Information Processing.
Original languageEnglish
TitleMultidisciplinary Research and Practice for Information Systems
EditorsGerald Quirchmayr, Josef Basl, Ilsun You, Lida Xu, Edgar Weippl
PublisherSpringer Verlag
Publication date2012
Pages624-638
ISBN (print)978-3-642-32497-0
DOIs
StatePublished

Conference

ConferenceInternational Cross-Domain Conference and Workshop on Availability, Reliability, and Security (CD-ARES 2012)
CountryCzech Republic
CityPrague
Period20-08-1224-08-12
NameLecture Notes in Computer Science
Volume7465
ISSN (Print)0302-9743
CitationsWeb of Science® Times Cited: No match on DOI

Keywords

  • Health care, Internet

ID: 12388692