Anomaly detection inspired by immune network theory: a proposal

Authors:
HuiKeng Lau;Jon Timmis;Iain Bate
Affiliations:
Department of Computer Science, University of York, Heslington, York, UK;Department of Computer Science and Department of Electronics, University of York, Heslington, York, UK;Department of Computer Science, University of York, Heslington, York, UK
Venue:
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Year:
2009

Citing 12
Cited 1

An Intrusion-Detection Model

IEEE Transactions on Software Engineering - Special issue on computer security and privacy
The immune system, adaptation, and machine learning

Physica D
Artificial Immune Systems: A New Computational Intelligence Paradigm

Artificial Immune Systems: A New Computational Intelligence Paradigm
Hints for Adaptive Problem Solving Gleaned from Immune Networks

PPSN I Proceedings of the 1st Workshop on Parallel Problem Solving from Nature
An Evolutionary Immune Network for Data Clustering

SBRN '00 Proceedings of the VI Brazilian Symposium on Neural Networks (SBRN'00)
Unsupervised anomaly detection in network intrusion detection using clusters

ACSC '05 Proceedings of the Twenty-eighth Australasian conference on Computer Science - Volume 38
A study in using neural networks for anomaly and misuse detection

SSYM'99 Proceedings of the 8th conference on USENIX Security Symposium - Volume 8
Research on hidden Markov model for system call anomaly detection

PAISI'07 Proceedings of the 2007 Pacific Asia conference on Intelligence and security informatics
Danger is ubiquitous: detecting malicious activities in sensor networks using the dendritic cell algorithm

ICARIS'06 Proceedings of the 5th international conference on Artificial Immune Systems
Unsupervised anomaly detection based n an evolutionary artificial immune network

EC'05 Proceedings of the 3rd European conference on Applications of Evolutionary Computing
Immune-Inspired Adaptable Error Detection for Automated Teller Machines

IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
A survey on sensor networks

IEEE Communications Magazine

An Immuno-engineering Approach for Anomaly Detection in Swarm Robotics

ICARIS '09 Proceedings of the 8th International Conference on Artificial Immune Systems

Quantified Score

Hi-index	0.00

Visualization

Abstract

Previous research in supervised and unsupervised anomaly detection normally employ a static model of normal behaviour (normal-model) throughout the lifetime of the system. However, there are real world applications such as swarm robotics and wireless sensor networks where what is perceived as normal behaviour changes accordingly to the changes in the environment. To cater for such systems, dynamically updating the normal-model is required. In this paper, we examine the requirements from a range of distributed autonomous systems and then propose a novel unsupervised anomaly detection architecture capable of online adaptation inspired by the vertebrate immune system.