DCA for bot detection

Yousof Al-Hammadi, Uwe Aickelin, Julie Greensmith

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

53 Scopus citations


Ensuring the security of computers is a nontrivial task, with many techniques used by malicious users to compromise these systems. In recent years a new threat has emerged in the form of networks of hijacked zombie machines used to perform complex distributed attacks such as denial of service and to obtain sensitive data such as password information. These zombie machines are said to be infected with a 'bot' - a malicious piece of software which is installed on a host machine and is controlled by a remote attacker, termed the 'botmaster of a botnet'. In this work, we use the biologically inspired Dendritic Cell Algorithm (DCA) to detect the existence of a single bot on a compromised host machine. The DCA is an immune-inspired algorithm based on an abstract model of the behaviour of the dendritic cells of the human body. The basis of anomaly detection performed by the DCA is facilitated using the correlation of behavioural attributes such as keylogging and packet flooding behaviour. The results of the application of the DCA to the detection of a single bot show that the algorithm is a successful technique for the detection of such malicious software without responding to normally running programs.

Original languageBritish English
Title of host publication2008 IEEE Congress on Evolutionary Computation, CEC 2008
Number of pages10
StatePublished - 2008
Event2008 IEEE Congress on Evolutionary Computation, CEC 2008 - Hong Kong, China
Duration: 1 Jun 20086 Jun 2008

Publication series

Name2008 IEEE Congress on Evolutionary Computation, CEC 2008


Conference2008 IEEE Congress on Evolutionary Computation, CEC 2008
CityHong Kong


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