Optimising IDS Sensor Placement

Hao Chen; John A. Clark; Siraj A. Shaikh; Howard Chivers; Philip Nobles

doi:10.1109/ARES.2010.92

Optimising IDS Sensor Placement

Hao Chen, John A. Clark, Siraj A. Shaikh, Howard Chivers, Philip Nobles

Computer Science

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

Abstract

In large network environments multiple intrusion detection sensors are needed to adequately monitor network traffic. However, deploying and managing additional sensors on a large network can be a demanding task, and organisations have to balance their desire for detecting intrusions throughout their network with financial and staffing limitations. This paper investigates how intrusion detection system (IDS) sensors should best be placed on a network when there are several competing evaluation criteria. This is a computationally difficult problem and we show how Multi-Objective Genetic Algorithms provide an excellent means of searching for optimal placements.

Original language	English
Title of host publication	FIFTH INTERNATIONAL CONFERENCE ON AVAILABILITY, RELIABILITY, AND SECURITY: ARES 2010, PROCEEDINGS
Place of Publication	LOS ALAMITOS
Publisher	IEEE Computer Society
Pages	315-320
Number of pages	6
ISBN (Print)	978-0-7695-3965-2
DOIs	https://doi.org/10.1109/ARES.2010.92
Publication status	Published - 2010
Event	5th International Conference on Availability, Reliability and Security - Cracow Duration: 15 Feb 2010 → 18 Feb 2010

Conference

Conference	5th International Conference on Availability, Reliability and Security
City	Cracow
Period	15/02/10 → 18/02/10

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10.1109/ARES.2010.92

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@inproceedings{e14838327fdf412b8035dd1c3fbdf9a1,

title = "Optimising IDS Sensor Placement",

abstract = "In large network environments multiple intrusion detection sensors are needed to adequately monitor network traffic. However, deploying and managing additional sensors on a large network can be a demanding task, and organisations have to balance their desire for detecting intrusions throughout their network with financial and staffing limitations. This paper investigates how intrusion detection system (IDS) sensors should best be placed on a network when there are several competing evaluation criteria. This is a computationally difficult problem and we show how Multi-Objective Genetic Algorithms provide an excellent means of searching for optimal placements.",

author = "Hao Chen and Clark, {John A.} and Shaikh, {Siraj A.} and Howard Chivers and Philip Nobles",

year = "2010",

doi = "10.1109/ARES.2010.92",

language = "English",

isbn = "978-0-7695-3965-2",

pages = "315--320",

booktitle = "FIFTH INTERNATIONAL CONFERENCE ON AVAILABILITY, RELIABILITY, AND SECURITY: ARES 2010, PROCEEDINGS",

publisher = "IEEE Computer Society",

address = "United States",

note = "5th International Conference on Availability, Reliability and Security ; Conference date: 15-02-2010 Through 18-02-2010",

}

Chen, H, Clark, JA, Shaikh, SA, Chivers, H & Nobles, P 2010, Optimising IDS Sensor Placement. in FIFTH INTERNATIONAL CONFERENCE ON AVAILABILITY, RELIABILITY, AND SECURITY: ARES 2010, PROCEEDINGS. IEEE Computer Society, LOS ALAMITOS, pp. 315-320, 5th International Conference on Availability, Reliability and Security, Cracow, 15/02/10. https://doi.org/10.1109/ARES.2010.92

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T1 - Optimising IDS Sensor Placement

AU - Chen, Hao

AU - Clark, John A.

AU - Shaikh, Siraj A.

AU - Chivers, Howard

AU - Nobles, Philip

PY - 2010

Y1 - 2010

N2 - In large network environments multiple intrusion detection sensors are needed to adequately monitor network traffic. However, deploying and managing additional sensors on a large network can be a demanding task, and organisations have to balance their desire for detecting intrusions throughout their network with financial and staffing limitations. This paper investigates how intrusion detection system (IDS) sensors should best be placed on a network when there are several competing evaluation criteria. This is a computationally difficult problem and we show how Multi-Objective Genetic Algorithms provide an excellent means of searching for optimal placements.

AB - In large network environments multiple intrusion detection sensors are needed to adequately monitor network traffic. However, deploying and managing additional sensors on a large network can be a demanding task, and organisations have to balance their desire for detecting intrusions throughout their network with financial and staffing limitations. This paper investigates how intrusion detection system (IDS) sensors should best be placed on a network when there are several competing evaluation criteria. This is a computationally difficult problem and we show how Multi-Objective Genetic Algorithms provide an excellent means of searching for optimal placements.

UR - http://www.scopus.com/inward/record.url?scp=77952332147&partnerID=8YFLogxK

U2 - 10.1109/ARES.2010.92

DO - 10.1109/ARES.2010.92

M3 - Conference contribution

SN - 978-0-7695-3965-2

SP - 315

EP - 320

BT - FIFTH INTERNATIONAL CONFERENCE ON AVAILABILITY, RELIABILITY, AND SECURITY: ARES 2010, PROCEEDINGS

PB - IEEE Computer Society

CY - LOS ALAMITOS

T2 - 5th International Conference on Availability, Reliability and Security

Y2 - 15 February 2010 through 18 February 2010

ER -

Optimising IDS Sensor Placement

Abstract

Conference

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