An Overview of Intrusion Detection Based on Data Mining Techniques

Author

Wankhade, K. ; Patka, S. ; Thool, R.

Author_Institution

Dept. of Inf. Technol., G.H. Raisoni Coll. of Eng., Nagpur, India

fYear

2013

fDate

6-8 April 2013

Firstpage

626

Lastpage

629

Abstract

Intrusion Detection System (IDS) is a vital component of any network in today´s world of Internet. IDS are an effective way to detect different kinds of attacks in interconnected network. An effective Intrusion Detection System requires high accuracy and detection rate as well as low false alarm rate. Different Data Mining techniques such as clustering and classification are proving to be useful for analyzing and dealing with large amount of network traffic. This paper presents various data mining techniques applied on intrusion detection systems for the effective identification of both known and unknown patterns of attacks, to develop secure information systems.

Keywords

data mining; pattern classification; pattern clustering; security of data; IDS; Internet; attack detection; attack pattern identification; classification; clustering; data mining; detection rate; false alarm rate; interconnected network; intrusion detection system; network traffic; secure information system; Classification algorithms; Clustering algorithms; Conferences; Data mining; Heuristic algorithms; Intrusion detection; Labeling; Intrusion detection system; classification; clustering; data mining; detection rate; false alarm rate;

fLanguage

English

Publisher

ieee

Conference_Titel

Communication Systems and Network Technologies (CSNT), 2013 International Conference on

Conference_Location

Gwalior

Print_ISBN

978-1-4673-5603-9

Type

conf

DOI

10.1109/CSNT.2013.134

Filename

6524477