The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.
A New Intrusion Detection System Based on KNN Classification Algorithm in Wireless Sensor Network
Open accessAbstract
The Internet of Things has broad application in military field, commerce, environmental monitoring, and many other fields. However, the open nature of the information media and the poor deployment environment have brought great risks to the security of wireless sensor networks, seriously restricting the application of wireless sensor network. Internet of Things composed of wireless sensor network faces security threats mainly from Dos attack, replay attack, integrity attack, false routing information attack, and flooding attack. In this paper, we proposed a new intrusion detection system based onK-nearest neighbor (K-nearest neighbor, referred to as KNN below) classification algorithm in wireless sensor network. This system can separate abnormal nodes from normal nodes by observing their abnormal behaviors, and we analyse parameter selection and error rate of the intrusion detection system. The paper elaborates on the design and implementation of the detection system. This system has achieved efficient, rapid intrusion detection by improving the wireless ad hoc on-demand distance vector routing protocol (Ad hoc On-Demand Distance the Vector Routing, AODV). Finally, the test results show that: the system has high detection accuracy and speed, in accordance with the requirement of wireless sensor network intrusion detection.
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Cites
Ad-hoc on-demand distance vector routing
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A key-management scheme for distributed sensor networks
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The Dynamic Source Routing Protocol for Mobile Ad Hoc Networks (DSR)
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The Dynamic Source Routing Protocol (DSR) for Mobile Ad Hoc Networks for IPv4
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Data Mining Approaches for Intrusion Detection
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Use of K-Nearest Neighbor classifier for intrusion detection
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PDA: Privacy-Preserving Data Aggregation in Wireless Sensor Networks
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A Provably Secure Additive and Multiplicative Privacy Homomorphism*
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A random perturbation-based scheme for pairwise key establishment in sensor networks
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Cited by
A Deep Learning Approach for Intrusion Detection Using Recurrent Neural Networks
Yin, C., Zhu, Y., Fei, J., & He, X. (2017) · IEEE Access · doi:10.1109/access.2017.2762418 · Cited by 2,100
A Survey of Machine and Deep Learning Methods for Internet of Things (IoT) Security
Al-Garadi, M. A., Mohamed, A., Al-Ali, A. K., Du, X., Ali, I., & Guizani, M. (2020) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2020.2988293 · Cited by 1,392
Machine learning algorithms for wireless sensor networks: A survey
Praveen Kumar, D., Amgoth, T., & Annavarapu, C. S. R. (2019) · Information Fusion · doi:10.1016/j.inffus.2018.09.013 · Cited by 687
BAT: Deep Learning Methods on Network Intrusion Detection Using NSL-KDD Dataset
Su, T., Sun, H., Zhu, J., Wang, S., & Li, Y. (2020) · IEEE Access · doi:10.1109/access.2020.2972627 · Cited by 434
Asharf, J., Moustafa, N., Khurshid, H., Debie, E., Haider, W., & Wahab, A. (2020) · Electronics · doi:10.3390/electronics9071177 · Cited by 378
Metadata
- Authors
- Li, W., Yi, P., Wu, Y., Pan, L., & Li, J.
- Venue
- Journal of Electrical and Computer Engineering
- Publisher
- Wiley
- Published
- 2014
- Volume
- 2014
- Pages
- 1-8
- ISSN
- 2090-0147 (ISSN-L)
- 2090-0155
- OpenAlex
- W2120685459
- Cited by
- 295
- References
- 12
- FWCI
- 6.55
- Type
- journal article
- Language
- en
- Open access
- gold
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- Li, W., Yi, P., Wu, Y., Pan, L., & Li, J. (2014). A New Intrusion Detection System Based on KNN Classification Algorithm in Wireless Sensor Network. Journal of Electrical and Computer Engineering. https://doi.org/10.1155/2014/240217
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