Can a Fuzzy Rule Extraction Find an Extremely Tiny non-Self Region?

Akira Imada

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Paper

Can a Fuzzy Rule Extraction Find an Extremely Tiny non-Self Region?

In Proceedings of the 1st International Workshop on Artificial Neural Networks and Intelligent Information Processing - Volume 0ICINCO, 35-41, 2005 , Barcelona, Spain

Author: Akira Imada

Affiliation: Brest State Technical University, Belarus

Abstract: This paper reports one snapshot of our on-going experiments in which a common target we call a-tiny-island-in-a-huge-lake is explored with different methods ranging from a data-mining technique to an artificial immune system. Our implicit interest is a network intrusion detection where we usually do not know what does an illegal transaction pattern look like until it completed intrusion when it was too late. Hence our first interest is (i) if it is possible to train the intrusion detection system only using legal patterns. From this context we assume data floating in the lake are normal while ones found on the island is abnormal. Our second concern is then (ii) to study the limit of the size of the detectable area, that is, until what size can the detector detect it when we decrease the size of the island shrinking to zero, which is sometimes called a-needle-in-a-haystack. In this paper, a fuzzy rule extraction implemented by a neural network architecture is employed for the purpose.

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Paper citation in several formats:

Imada, A. (2005). Can a Fuzzy Rule Extraction Find an Extremely Tiny non-Self Region?. In Proceedings of the 1st International Workshop on Artificial Neural Networks and Intelligent Information Processing (ICINCO 2005) - ANNIIP; ISBN 972-8865-36-8, SciTePress, pages 35-41. DOI: 10.5220/0001197000350041

@conference{anniip05,
author={Akira Imada.},
title={Can a Fuzzy Rule Extraction Find an Extremely Tiny non-Self Region?},
booktitle={Proceedings of the 1st International Workshop on Artificial Neural Networks and Intelligent Information Processing (ICINCO 2005) - ANNIIP},
year={2005},
pages={35-41},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001197000350041},
isbn={972-8865-36-8},
}

TY - CONF

JO - Proceedings of the 1st International Workshop on Artificial Neural Networks and Intelligent Information Processing (ICINCO 2005) - ANNIIP
TI - Can a Fuzzy Rule Extraction Find an Extremely Tiny non-Self Region?
SN - 972-8865-36-8
AU - Imada, A.
PY - 2005
SP - 35
EP - 41
DO - 10.5220/0001197000350041
PB - SciTePress