Skip to main content

Research Repository

Advanced Search

Outputs (40)

Introducting Dendritic Cells as a Novel Immune-Inspired Algorithm for Anomaly Detection
Presentation / Conference Contribution
Greensmith, J., Aickelin, U., & Cayzer, S. Introducting Dendritic Cells as a Novel Immune-Inspired Algorithm for Anomaly Detection. Presented at Proceedings of the 4th International Conference on Artificial Immune Systems (ICARIS 2005)

Dendritic cells are antigen presenting cells that provide a
vital link between the innate and adaptive immune system. Research into this family of cells has revealed that they perform the role of coordinating T-cell based immune responses, both reac... Read More about Introducting Dendritic Cells as a Novel Immune-Inspired Algorithm for Anomaly Detection.

An Agent-based Classification Model
Presentation / Conference Contribution
Gu, F., Aickelin, U., & Greensmith, J. An Agent-based Classification Model. Presented at The 9th European Agent Systems Summer School (EASSS 2007)

The major function of this model is to access the UCI Wisconsin Breast Cancer data-set[1] and classify the data items into two categories, which are normal
and anomalous. This kind of classification can be referred as anomaly detection, which discri... Read More about An Agent-based Classification Model.

Dendritic Cells for SYN Scan Detection
Presentation / Conference Contribution
Greensmith, J., & Aickelin, U. Dendritic Cells for SYN Scan Detection. Presented at Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2007)

Artificial immune systems have previously been applied to the problem of intrusion detection. The aim of this research is to develop an intrusion detection system based on the function of Dendritic Cells (DCs). DCs are antigen presenting cells and ke... Read More about Dendritic Cells for SYN Scan Detection.

The DCA:SOMe comparison: a comparative study between two biologically-inspired algorithms
Journal Article
Greensmith, J., Feyereisl, J., & Aickelin, U. The DCA:SOMe comparison: a comparative study between two biologically-inspired algorithms. Evolutionary Intelligence, 1(2), https://doi.org/10.1007/s12065-008-0008-6

The dendritic cell algorithm (DCA) is an immune-inspired algorithm, developed for the purpose of anomaly detection. The algorithm performs multi-sensor data fusion and correlation which results in a ‘context aware’ detection system. Previous applicat... Read More about The DCA:SOMe comparison: a comparative study between two biologically-inspired algorithms.

The deterministic Dendritic Cell Algorithm
Presentation / Conference Contribution
Greensmith, J., & Aickelin, U. The deterministic Dendritic Cell Algorithm. Presented at 7th International Conference on Artificial Immune Systems (ICARIS2008)

The Dendritic Cell Algorithm is an immune-inspired algorithm originally based on the function of natural dendritic cells. The original instantiation of the algorithm is a highly stochastic algorithm. While the performance of the algorithm is good whe... Read More about The deterministic Dendritic Cell Algorithm.

PCA 4 DCA: the application of principal component analysis to the Dendritic Cell Algorithm
Presentation / Conference Contribution
Gu, F., Greensmith, J., Oates, R., & Aickelin, U. PCA 4 DCA: the application of principal component analysis to the Dendritic Cell Algorithm. Presented at 9th Annual Workshop on Computational Intelligence (UKCI 2009)

As one of the newest members in the field of articial immune systems (AIS), the Dendritic Cell Algorithm (DCA) is
based on behavioural models of natural dendritic cells (DCs). Unlike other AIS, the DCA does not rely on training data, instead domain... Read More about PCA 4 DCA: the application of principal component analysis to the Dendritic Cell Algorithm.

On the role of the AIS practitioner
Presentation / Conference Contribution
Hart, E., Read, M., McEwan, C., Aickelin, U., & Greensmith, J. On the role of the AIS practitioner. Presented at The 12th European Conference on Artificial Life (ECAL 2013)

Cognisant of the gulf between engineers and immunologists
that currenty hinders a truly inter-disciplinary approach to
the field of Artificial Immune Systems (AIS), we propose
a redefinition of the term AIS practitioner, as an individual who ident... Read More about On the role of the AIS practitioner.

Variance in system dynamics and agent based modelling using the SIR model of infectious diseases
Presentation / Conference Contribution
Ahmed, A., Greensmith, J., & Aickelin, U. Variance in system dynamics and agent based modelling using the SIR model of infectious diseases. Presented at Proceedings of the 26th European Conference on Modelling and Simulation (ECMS)

Classical deterministic simulations of epidemiological processes, such as those based on System Dynamics, produce a single result based on a fixed set of input parameters with no variance between simulations. Input parameters are subsequently modifie... Read More about Variance in system dynamics and agent based modelling using the SIR model of infectious diseases.

Integrating real-time analysis with the dendritic cell algorithm through segmentation
Presentation / Conference Contribution
Gu, F., Greensmith, J., & Aickelin, U. Integrating real-time analysis with the dendritic cell algorithm through segmentation. Presented at GECCO '09: Proceedings of the 11th Genetic and Evolutionary Computation Conference

As an immune inspired algorithm, the Dendritic Cell Algorithm (DCA) has been applied to a range of problems, particularly in the area of intrusion detection. Ideally, the intrusion detection should be performed in real-time, to continuously detect mi... Read More about Integrating real-time analysis with the dendritic cell algorithm through segmentation.