An intrusion detection method for wireless sensor network based on mathematical morphology. Issue 15 (11th February 2015)
- Record Type:
- Journal Article
- Title:
- An intrusion detection method for wireless sensor network based on mathematical morphology. Issue 15 (11th February 2015)
- Main Title:
- An intrusion detection method for wireless sensor network based on mathematical morphology
- Authors:
- Wang, Yanwen
Wu, Xiaoling
Chen, Hainan - Abstract:
- Abstract: Security issue in Internet of Things (IoTs) has long been the topic of extensive research in the last decade. Data encryption and authentication are the most common two methods to address the security issues in IoTs. However, these efforts are ineffective in detecting the diverse malicious attacks, especially in intrusion detection. Comparatively, very few attentions have been paid for detecting intrusive nodes in IoTs research. Therefore, in this paper, we derive an innovative method called granulometric size distribution (GSD) method based on mathematical morphology for detecting malicious attack in IoTs, such as intrusion detection. We successfully generate GSD clusters to directly monitor the number of active nodes in a wireless sensor network because the GSD curves are similar when the number of active nodes in a wireless sensor network is fixed. Link Quality Indicator data of each node are utilized as the network parameters in this method. The results show the effectiveness in intrusion detection. Copyright © 2015 John Wiley & Sons, Ltd. Abstract : In this paper, " An intrusion detection method for wireless sensor network based on mathematical morphology" written by Yanwen Wang, Xiaoling Wu * and Hainan Chen, an innovative method called Granulometric Size Distribution (GSD) method is proposed based on mathematical morphology for detecting malicious attack in IoTs. GSD clusters are successfully generated to monitor the number of active nodes in a wirelessAbstract: Security issue in Internet of Things (IoTs) has long been the topic of extensive research in the last decade. Data encryption and authentication are the most common two methods to address the security issues in IoTs. However, these efforts are ineffective in detecting the diverse malicious attacks, especially in intrusion detection. Comparatively, very few attentions have been paid for detecting intrusive nodes in IoTs research. Therefore, in this paper, we derive an innovative method called granulometric size distribution (GSD) method based on mathematical morphology for detecting malicious attack in IoTs, such as intrusion detection. We successfully generate GSD clusters to directly monitor the number of active nodes in a wireless sensor network because the GSD curves are similar when the number of active nodes in a wireless sensor network is fixed. Link Quality Indicator data of each node are utilized as the network parameters in this method. The results show the effectiveness in intrusion detection. Copyright © 2015 John Wiley & Sons, Ltd. Abstract : In this paper, " An intrusion detection method for wireless sensor network based on mathematical morphology" written by Yanwen Wang, Xiaoling Wu * and Hainan Chen, an innovative method called Granulometric Size Distribution (GSD) method is proposed based on mathematical morphology for detecting malicious attack in IoTs. GSD clusters are successfully generated to monitor the number of active nodes in a wireless sensor network because the GSD curves are similar when the number of active nodes in a wireless sensor network isfixed. … (more)
- Is Part Of:
- Security and communication networks. Volume 9:Issue 15(2016)
- Journal:
- Security and communication networks
- Issue:
- Volume 9:Issue 15(2016)
- Issue Display:
- Volume 9, Issue 15 (2016)
- Year:
- 2016
- Volume:
- 9
- Issue:
- 15
- Issue Sort Value:
- 2016-0009-0015-0000
- Page Start:
- 2744
- Page End:
- 2751
- Publication Date:
- 2015-02-11
- Subjects:
- internet of things (IoTs) -- intrusion detection -- mathematical morphology (MM) -- GSD -- LQI
Computer networks -- Security measures -- Periodicals
Computer security -- Periodicals
Cryptography -- Periodicals
005.805 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1939-0122 ↗
https://www.hindawi.com/journals/scn/ ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1002/sec.1181 ↗
- Languages:
- English
- ISSNs:
- 1939-0114
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 2779.xml