Published on Mon Mar 01 2010

Further Exploration of the Dendritic Cell Algorithm: Antigen Multiplier and Time Windows

Feng Gu, Julie Greensmith, Uwe Aickelin

The Dendritic Cell Algorithm (DCA) produces promising performances in the field of anomaly detection. This paper presents the application of the DCA to a standard data set, the KDD 99 data set.

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Abstract

As an immune-inspired algorithm, the Dendritic Cell Algorithm (DCA), produces promising performances in the field of anomaly detection. This paper presents the application of the DCA to a standard data set, the KDD 99 data set. The results of different implementation versions of the DXA, including the antigen multiplier and moving time windows are reported. The real-valued Negative Selection Algorithm (NSA) using constant-sized detectors and the C4.5 decision tree algorithm are used, to conduct a baseline comparison. The results suggest that the DCA is applicable to KDD 99 data set, and the antigen multiplier and moving time windows have the same effect on the DCA for this particular data set. The real-valued NSA with constant-sized detectors is not applicable to the data set, and the C4.5 decision tree algorithm provides a benchmark of the classification performance for this data set.

Thu Jan 14 2010
Neural Networks
Dendritic Cells for Anomaly Detection
Dendritic Cells (DCs) are key to the activation of the human signals. DCs perform multi-sensor data fusion based on time-windows. The behaviour of human DCs is abstracted to form the DCAlgorithm (DCA)
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Fri May 31 2013
Neural Networks
The Dendritic Cell Algorithm for Intrusion Detection
Artificial Immune Systems (AIS) have shown their advantages. Among them, the Dendritic Cell Algorithm (DCA) has produced promising results. The aim of this chapter is to demonstrate the potential for the DCA as a suitable candidate for intrusion detection problems.
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Thu Jul 04 2013
Machine Learning
Quiet in Class: Classification, Noise and the Dendritic Cell Algorithm
Theoretical analyses of the Dendritic Cell Algorithm (DCA) have yielded several criticisms about its underlying structure and operation. A contribution of this work is to investigate the effects of replacing the classification stage of the DCA with a traditional machine learning technique.
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Mon Mar 22 2010
Neural Networks
Integrating Real-Time Analysis With The Dendritic Cell Algorithm Through Segmentation
The Dendritic Cell Algorithm (DCA) has been applied to a range of problems. The analysis process of the DCA is currently performed offline. To improve the algorithm's performance we suggest the development of a real-time analysis component.
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Mon Mar 01 2010
Artificial Intelligence
Exploration Of The Dendritic Cell Algorithm Using The Duration Calculus
The Dendritic Cell Algorithm (DCA) has been applied to a range of problems. However, the analysis process of the standard DCA constricts its real-time capability. As a result, the DCA should be replaced by a real- time analysis component.
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Fri Jun 25 2010
Neural Networks
Detecting Danger: The Dendritic Cell Algorithm
The Dendritic Cell Algorithm (DCA) is inspired by the function of the human immune system. The DCA is a population based algorithm, with each agent in the system represented as an 'artificial DC'
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