A Novel Survey on Intrusion Detection using Data Mining

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IJCA Proceedings on International Conference on Advances in Science and Technology
© 2015 by IJCA Journal
ICAST 2014 - Number 4
Year of Publication: 2015
Authors:
Purtata Bhoir
Shilpa Kolte

Purtata Bhoir and Shilpa Kolte. Article: A Novel Survey on Intrusion Detection using Data Mining. IJCA Proceedings on International Conference on Advances in Science and Technology ICAST 2014(4):26-29, February 2015. Full text available. BibTeX

@article{key:article,
	author = {Purtata Bhoir and Shilpa Kolte},
	title = {Article: A Novel Survey on Intrusion Detection using Data Mining},
	journal = {IJCA Proceedings on International Conference on Advances in Science and Technology},
	year = {2015},
	volume = {ICAST 2014},
	number = {4},
	pages = {26-29},
	month = {February},
	note = {Full text available}
}

Abstract

Database security is vital nowadays as database system contain valuable information. In today's computer world, attacks are used to disclose, destroy, alter, or steal information. The information security plays vital role to protect confidentiality, integrity and availability of information. Intrusion detection system (IDS) is one of the important components of strong information security system. IDS serve three security functions: they monitor, detect and respond to unauthorized activity. Researchers are working on various data mining techniques such as access patterns of users, data dependencies to detect malicious attacks. Data mining is widely used to find useful patterns from large volume of data. In this paper we have enlisted some existing ID approaches of data mining for detecting insider attacks and compared them with considering their advantages and disadvantages.

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