Skip to main content

Research Repository

See what's under the surface

Advanced Search

DCA for bot detection

Al-Hammadi, Yousof; Aickelin, Uwe; Greensmith, Julie

Authors

Yousof Al-Hammadi

Uwe Aickelin

Julie Greensmith



Abstract

Ensuring the security of computers is a non-trivial 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 dasiahotpsila - a malicious piece of software which is installed on a host machine and is controlled by a remote attacker, termed the dasiabotmaster of a botnetpsila. In this work, we use the biologically inspired dendritic cell algorithm (DCA) to detect the existence of a single hot 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 hot show that the algorithm is a successful technique for the detection of such malicious software without responding to normally running programs.

Publication Date Jan 1, 2008
Journal Proceedings of the IEEE World Congress on Computational Intelligence (WCCI2008), Hong Kong
Peer Reviewed Peer Reviewed
Book Title IEEE Congress on Evolutionary Computation, 2008: CEC 2008
APA6 Citation Al-Hammadi, Y., Aickelin, U., & Greensmith, J. (2008). DCA for bot detection. In IEEE Congress on Evolutionary Computation, 2008: CEC 2008IEEE
Publisher URL http://ieeexplore.ieee.org/xpl/tocresult.jsp?isnumber=4630767&isYear=2008&count=604&page=10&ResultStart=250
Related Public URLs http://www.wcci2008.org/
Copyright Statement Copyright information regarding this work can be found at the following address: http://eprints.nottingh.../end_user_agreement.pdf
Additional Information Originally presented at the IEEE World Conference on Computational Intelligence, held in Hong Kong, 6-8 June 2008.

Files

al-hammadi2008.pdf (177 Kb)
PDF

Copyright Statement
Copyright information regarding this work can be found at the following address: http://eprints.nottingham.ac.uk/end_user_agreement.pdf





You might also like



Downloadable Citations

;