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Effective Fast and Fuzzy Art Map Performance to Detect Intrusion

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IJCA Proceedings on National Conference on Advances in Computing
© 2015 by IJCA Journal
NCAC 2015 - Number 3
Year of Publication: 2015
Authors:
Swati A Sonawale
Roshani Ade

Swati A Sonawale and Roshani Ade. Article: Effective Fast and Fuzzy Art Map Performance to Detect Intrusion. IJCA Proceedings on National Conference on Advances in Computing NCAC 2015(3):29-33, December 2015. Full text available. BibTeX

@article{key:article,
	author = {Swati A Sonawale and Roshani Ade},
	title = {Article: Effective Fast and Fuzzy Art Map Performance to Detect Intrusion},
	journal = {IJCA Proceedings on National Conference on Advances in Computing},
	year = {2015},
	volume = {NCAC 2015},
	number = {3},
	pages = {29-33},
	month = {December},
	note = {Full text available}
}

Abstract

Great research work have been conducted towards Intrusion Detection Systems (IDSs) as well as feature selection. Feature selection applications have a great influence on decreasing development lead times and increasing product quality as well as proficiency. IDS guards a system from attack, misuse, and compromise. It can also screen network action. Network traffic observing and extent is progressively regarded as a key role for understanding and improving the performance and security of our cyber infrastructure. By using IDS attack can be detected in system as info is vital strength for every business. It can cause millions of harm within a few seconds. Security is important factor because reputation of business depends on it. So timely detection of intrusion is important so that preventive actions can be taken. IDS framework has been proposed by using fuzzy feature selection method with ARTMAP. It has been observed that the proposed framework gives better accuracy in less time as compared to methods in literature.

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