A two-stage hybrid model for intrusion detection

Krishnamoorthi; N. V.Subba Reddy; U. Dinesh Acharya

doi:10.1109/ADCOM.2006.4289875

A two-stage hybrid model for intrusion detection

Krishnamoorthi, N. V.Subba Reddy, U. Dinesh Acharya

Department of Computer Science and Engineering, Manipal Institute of Technology, Manipal

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

As the number of networked computers grows, intrusion detection is an essential component in keeping networks secure. Various approaches to intrusion detection are currently being in use with each one has its own merits and demerits. This paper presents a hybrid approach for modeling intrusion detection system (IDS). Rule based classifier and simple K-means clustering are combined as a hybrid intelligent system. The initial prototype developed by the rule base classifier improves the performance of K-means clustering. The results show that the developed hybrid model provides better IDS.

Original language	English
Title of host publication	Proceedings - 2006 14th International Conference on Advanced Computing and Communications, ADCOM 2006
Pages	163-165
Number of pages	3
DOIs	https://doi.org/10.1109/ADCOM.2006.4289875
Publication status	Published - 2006
Event	14th International Conference on Advanced Computing and Communications, ADCOM 2006 - Surathkal, India Duration: 20-12-2006 → 23-12-2006

Conference

Conference	14th International Conference on Advanced Computing and Communications, ADCOM 2006
Country/Territory	India
City	Surathkal
Period	20-12-06 → 23-12-06

All Science Journal Classification (ASJC) codes

Computer Networks and Communications
Communication

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10.1109/ADCOM.2006.4289875

Cite this

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title = "A two-stage hybrid model for intrusion detection",

abstract = "As the number of networked computers grows, intrusion detection is an essential component in keeping networks secure. Various approaches to intrusion detection are currently being in use with each one has its own merits and demerits. This paper presents a hybrid approach for modeling intrusion detection system (IDS). Rule based classifier and simple K-means clustering are combined as a hybrid intelligent system. The initial prototype developed by the rule base classifier improves the performance of K-means clustering. The results show that the developed hybrid model provides better IDS.",

author = "Krishnamoorthi and Reddy, {N. V.Subba} and Acharya, {U. Dinesh}",

year = "2006",

doi = "10.1109/ADCOM.2006.4289875",

language = "English",

isbn = "142440715X",

pages = "163--165",

booktitle = "Proceedings - 2006 14th International Conference on Advanced Computing and Communications, ADCOM 2006",

note = "14th International Conference on Advanced Computing and Communications, ADCOM 2006 ; Conference date: 20-12-2006 Through 23-12-2006",

}

Krishnamoorthi, , Reddy, NVS & Acharya, UD 2006, A two-stage hybrid model for intrusion detection. in Proceedings - 2006 14th International Conference on Advanced Computing and Communications, ADCOM 2006., 4289875, pp. 163-165, 14th International Conference on Advanced Computing and Communications, ADCOM 2006, Surathkal, India, 20-12-06. https://doi.org/10.1109/ADCOM.2006.4289875

TY - GEN

T1 - A two-stage hybrid model for intrusion detection

AU - Krishnamoorthi,

AU - Reddy, N. V.Subba

AU - Acharya, U. Dinesh

PY - 2006

Y1 - 2006

N2 - As the number of networked computers grows, intrusion detection is an essential component in keeping networks secure. Various approaches to intrusion detection are currently being in use with each one has its own merits and demerits. This paper presents a hybrid approach for modeling intrusion detection system (IDS). Rule based classifier and simple K-means clustering are combined as a hybrid intelligent system. The initial prototype developed by the rule base classifier improves the performance of K-means clustering. The results show that the developed hybrid model provides better IDS.

AB - As the number of networked computers grows, intrusion detection is an essential component in keeping networks secure. Various approaches to intrusion detection are currently being in use with each one has its own merits and demerits. This paper presents a hybrid approach for modeling intrusion detection system (IDS). Rule based classifier and simple K-means clustering are combined as a hybrid intelligent system. The initial prototype developed by the rule base classifier improves the performance of K-means clustering. The results show that the developed hybrid model provides better IDS.

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U2 - 10.1109/ADCOM.2006.4289875

DO - 10.1109/ADCOM.2006.4289875

M3 - Conference contribution

AN - SCOPUS:47649109177

SN - 142440715X

SN - 9781424407156

SP - 163

EP - 165

BT - Proceedings - 2006 14th International Conference on Advanced Computing and Communications, ADCOM 2006

T2 - 14th International Conference on Advanced Computing and Communications, ADCOM 2006

Y2 - 20 December 2006 through 23 December 2006

ER -

A two-stage hybrid model for intrusion detection

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