Secure Knowledge and Cluster-Based Intrusion Detection Mechanism for Smart Wireless Sensor Networks

Amjad Mehmood, Akbar Khanan, Muhammad Muneer Umar, Salwani Abdullah, Khairul Akram Zainol Ariffin , Houbing Song

Research output: Contribution to journalArticle

11 Citations (Scopus)

Abstract

Wireless sensor networks, due to their nature, are more prone to security threats than other networks. Developments in WSNs have led to the introduction of many protocols specially developed for security purposes. Most of these protocols are not efficient in terms of putting an excessive computational and energy consumption burden on small nodes in WSNs. This paper proposes a knowledge-based context-aware approach for handling the intrusions generated by malicious nodes. The system operates on a knowledge base, located at the base station, which is used to store the events generated by the nodes inside the network. The events are categorized and the cluster heads (CHs) are acknowledged to block maliciously repeated activities generated. The CHs can also get informational records about the maliciousness of intruder nodes by using their inference engines. The mechanism of events logging and analysis by the base station greatly affects the performance of nodes in the network by reducing the extra security-related load on them.

Original languageEnglish
Pages (from-to)5688-5694
Number of pages7
JournalIEEE Access
Volume6
DOIs
Publication statusPublished - 2 Nov 2017

Fingerprint

Intrusion detection
Base stations
Wireless sensor networks
Network protocols
Inference engines
Energy utilization

Keywords

  • cluster based WSN
  • Intrusion detection system
  • knowledge base
  • security

ASJC Scopus subject areas

  • Computer Science(all)
  • Materials Science(all)
  • Engineering(all)

Cite this

Secure Knowledge and Cluster-Based Intrusion Detection Mechanism for Smart Wireless Sensor Networks. / Mehmood, Amjad; Khanan, Akbar; Umar, Muhammad Muneer; Abdullah, Salwani; Zainol Ariffin , Khairul Akram; Song, Houbing.

In: IEEE Access, Vol. 6, 02.11.2017, p. 5688-5694.

Research output: Contribution to journalArticle

Mehmood, Amjad ; Khanan, Akbar ; Umar, Muhammad Muneer ; Abdullah, Salwani ; Zainol Ariffin , Khairul Akram ; Song, Houbing. / Secure Knowledge and Cluster-Based Intrusion Detection Mechanism for Smart Wireless Sensor Networks. In: IEEE Access. 2017 ; Vol. 6. pp. 5688-5694.
@article{7aedb37533614d439130405934d2aba3,
title = "Secure Knowledge and Cluster-Based Intrusion Detection Mechanism for Smart Wireless Sensor Networks",
abstract = "Wireless sensor networks, due to their nature, are more prone to security threats than other networks. Developments in WSNs have led to the introduction of many protocols specially developed for security purposes. Most of these protocols are not efficient in terms of putting an excessive computational and energy consumption burden on small nodes in WSNs. This paper proposes a knowledge-based context-aware approach for handling the intrusions generated by malicious nodes. The system operates on a knowledge base, located at the base station, which is used to store the events generated by the nodes inside the network. The events are categorized and the cluster heads (CHs) are acknowledged to block maliciously repeated activities generated. The CHs can also get informational records about the maliciousness of intruder nodes by using their inference engines. The mechanism of events logging and analysis by the base station greatly affects the performance of nodes in the network by reducing the extra security-related load on them.",
keywords = "cluster based WSN, Intrusion detection system, knowledge base, security",
author = "Amjad Mehmood and Akbar Khanan and Umar, {Muhammad Muneer} and Salwani Abdullah and {Zainol Ariffin }, {Khairul Akram} and Houbing Song",
year = "2017",
month = "11",
day = "2",
doi = "10.1109/ACCESS.2017.2770020",
language = "English",
volume = "6",
pages = "5688--5694",
journal = "IEEE Access",
issn = "2169-3536",
publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

TY - JOUR

T1 - Secure Knowledge and Cluster-Based Intrusion Detection Mechanism for Smart Wireless Sensor Networks

AU - Mehmood, Amjad

AU - Khanan, Akbar

AU - Umar, Muhammad Muneer

AU - Abdullah, Salwani

AU - Zainol Ariffin , Khairul Akram

AU - Song, Houbing

PY - 2017/11/2

Y1 - 2017/11/2

N2 - Wireless sensor networks, due to their nature, are more prone to security threats than other networks. Developments in WSNs have led to the introduction of many protocols specially developed for security purposes. Most of these protocols are not efficient in terms of putting an excessive computational and energy consumption burden on small nodes in WSNs. This paper proposes a knowledge-based context-aware approach for handling the intrusions generated by malicious nodes. The system operates on a knowledge base, located at the base station, which is used to store the events generated by the nodes inside the network. The events are categorized and the cluster heads (CHs) are acknowledged to block maliciously repeated activities generated. The CHs can also get informational records about the maliciousness of intruder nodes by using their inference engines. The mechanism of events logging and analysis by the base station greatly affects the performance of nodes in the network by reducing the extra security-related load on them.

AB - Wireless sensor networks, due to their nature, are more prone to security threats than other networks. Developments in WSNs have led to the introduction of many protocols specially developed for security purposes. Most of these protocols are not efficient in terms of putting an excessive computational and energy consumption burden on small nodes in WSNs. This paper proposes a knowledge-based context-aware approach for handling the intrusions generated by malicious nodes. The system operates on a knowledge base, located at the base station, which is used to store the events generated by the nodes inside the network. The events are categorized and the cluster heads (CHs) are acknowledged to block maliciously repeated activities generated. The CHs can also get informational records about the maliciousness of intruder nodes by using their inference engines. The mechanism of events logging and analysis by the base station greatly affects the performance of nodes in the network by reducing the extra security-related load on them.

KW - cluster based WSN

KW - Intrusion detection system

KW - knowledge base

KW - security

UR - http://www.scopus.com/inward/record.url?scp=85033662101&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85033662101&partnerID=8YFLogxK

U2 - 10.1109/ACCESS.2017.2770020

DO - 10.1109/ACCESS.2017.2770020

M3 - Article

AN - SCOPUS:85033662101

VL - 6

SP - 5688

EP - 5694

JO - IEEE Access

JF - IEEE Access

SN - 2169-3536

ER -