Lightweight Anomaly Detection for Wireless Sensor Networks
Anomaly detection in wireless sensor networks (WSNs) is critical to ensure the quality of senor data, secure monitoring, and reliable detection of interesting and critical events. The main challenge of anomaly detection algorithm in WSNs is identifying anomalies with high accuracy while consuming mi...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Hindawi - SAGE Publishing
2015-08-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1155/2015/653232 |
| _version_ | 1826998596106452992 |
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| author | Pu Cheng Minghua Zhu |
| author_facet | Pu Cheng Minghua Zhu |
| author_sort | Pu Cheng |
| collection | DOAJ |
| description | Anomaly detection in wireless sensor networks (WSNs) is critical to ensure the quality of senor data, secure monitoring, and reliable detection of interesting and critical events. The main challenge of anomaly detection algorithm in WSNs is identifying anomalies with high accuracy while consuming minimal resource of the network. In this paper two lightweight anomaly detection algorithms LADS and LADQA are proposed for WSNs. Both algorithms utilize the one-class quarter-sphere support vector machine (QSSVM) and convert the linear optimization problem of QSSVM to a sort problem for the reduced computational complexity. Experimental results show that the proposed algorithms can keep the lower computational complexity without reducing the accuracy for anomaly detection, compared to QSSVM. |
| first_indexed | 2024-03-12T09:29:32Z |
| format | Article |
| id | doaj.art-c33bcaa93826472aab9077ef8862baf6 |
| institution | Directory Open Access Journal |
| issn | 1550-1477 |
| language | English |
| last_indexed | 2025-02-18T10:16:44Z |
| publishDate | 2015-08-01 |
| publisher | Hindawi - SAGE Publishing |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj.art-c33bcaa93826472aab9077ef8862baf62024-11-02T05:32:05ZengHindawi - SAGE PublishingInternational Journal of Distributed Sensor Networks1550-14772015-08-011110.1155/2015/653232653232Lightweight Anomaly Detection for Wireless Sensor NetworksPu Cheng0Minghua Zhu1 Software Institute, Henan University, Kaifeng 475002, China Software Engineering Institute, East China Normal University, Shanghai 200062, ChinaAnomaly detection in wireless sensor networks (WSNs) is critical to ensure the quality of senor data, secure monitoring, and reliable detection of interesting and critical events. The main challenge of anomaly detection algorithm in WSNs is identifying anomalies with high accuracy while consuming minimal resource of the network. In this paper two lightweight anomaly detection algorithms LADS and LADQA are proposed for WSNs. Both algorithms utilize the one-class quarter-sphere support vector machine (QSSVM) and convert the linear optimization problem of QSSVM to a sort problem for the reduced computational complexity. Experimental results show that the proposed algorithms can keep the lower computational complexity without reducing the accuracy for anomaly detection, compared to QSSVM.https://doi.org/10.1155/2015/653232 |
| spellingShingle | Pu Cheng Minghua Zhu Lightweight Anomaly Detection for Wireless Sensor Networks International Journal of Distributed Sensor Networks |
| title | Lightweight Anomaly Detection for Wireless Sensor Networks |
| title_full | Lightweight Anomaly Detection for Wireless Sensor Networks |
| title_fullStr | Lightweight Anomaly Detection for Wireless Sensor Networks |
| title_full_unstemmed | Lightweight Anomaly Detection for Wireless Sensor Networks |
| title_short | Lightweight Anomaly Detection for Wireless Sensor Networks |
| title_sort | lightweight anomaly detection for wireless sensor networks |
| url | https://doi.org/10.1155/2015/653232 |
| work_keys_str_mv | AT pucheng lightweightanomalydetectionforwirelesssensornetworks AT minghuazhu lightweightanomalydetectionforwirelesssensornetworks |