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WSN-DS: A Dataset for Intrusion Detection Systems in Wireless Sensor Networks
Joint Authors
Al-Kasasbeh, Bassam
Almomani, Iman
al-Akhras, Mousa
Source
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-16, 16 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-09-29
Country of Publication
Egypt
No. of Pages
16
Main Subjects
Abstract EN
Wireless Sensor Networks (WSN) have become increasingly one of the hottest research areas in computer science due to their wide range of applications including critical military and civilian applications.
Such applications have created various security threats, especially in unattended environments.
To ensure the security and dependability of WSN services, an Intrusion Detection System (IDS) should be in place.
This IDS has to be compatible with the characteristics of WSNs and capable of detecting the largest possible number of security threats.
In this paper a specialized dataset for WSN is developed to help better detect and classify four types of Denial of Service (DoS) attacks: Blackhole, Grayhole, Flooding, and Scheduling attacks.
This paper considers the use of LEACH protocol which is one of the most popular hierarchical routing protocols in WSNs.
A scheme has been defined to collect data from Network Simulator 2 (NS-2) and then processed to produce 23 features.
The collected dataset is called WSN-DS.
Artificial Neural Network (ANN) has been trained on the dataset to detect and classify different DoS attacks.
The results show that WSN-DS improved the ability of IDS to achieve higher classification accuracy rate.
WEKA toolbox was used with holdout and 10-Fold Cross Validation methods.
The best results were achieved with 10-Fold Cross Validation with one hidden layer.
The classification accuracies of attacks were 92.8%, 99.4%, 92.2%, 75.6%, and 99.8% for Blackhole, Flooding, Scheduling, and Grayhole attacks, in addition to the normal case (without attacks), respectively.
American Psychological Association (APA)
Almomani, Iman& Al-Kasasbeh, Bassam& al-Akhras, Mousa. 2016. WSN-DS: A Dataset for Intrusion Detection Systems in Wireless Sensor Networks. Journal of Sensors،Vol. 2016, no. 2016, pp.1-16.
https://search.emarefa.net/detail/BIM-1110479
Modern Language Association (MLA)
Almomani, Iman…[et al.]. WSN-DS: A Dataset for Intrusion Detection Systems in Wireless Sensor Networks. Journal of Sensors No. 2016 (2016), pp.1-16.
https://search.emarefa.net/detail/BIM-1110479
American Medical Association (AMA)
Almomani, Iman& Al-Kasasbeh, Bassam& al-Akhras, Mousa. WSN-DS: A Dataset for Intrusion Detection Systems in Wireless Sensor Networks. Journal of Sensors. 2016. Vol. 2016, no. 2016, pp.1-16.
https://search.emarefa.net/detail/BIM-1110479
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1110479