Name
Abstract | ||
|---|---|---|
Wireless sensor networks (WSN) are increasingly used to support critical applications - especially in enterprise settings. If the sensor data collected through the network is incorrect, such applications cannot run reliably. Thus, detecting the occurrence of abnormal sensor values is crucial. In this paper we develop three decentralized, lightweight data anomaly detection mechanisms that can be run directly on sensor nodes. These algorithms are evaluated with a real dataset to which we added plausible attacks. Further, they are compared to standard centralized anomaly detection mechanisms. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/GreenCom.2012.132 | Green Computing and Communications |
Keywords | Field | DocType |
enterprise setting,data-centric intrusion detection,sensor node,wireless sensor network,plausible attack,critical application,abnormal sensor value,sensor data,wireless sensor networks,standard centralized anomaly detection,detection mechanism,lightweight data,data handling,learning artificial intelligence | Anomaly detection,Key distribution in wireless sensor networks,Computer science,Soft sensor,Visual sensor network,Computer network,Mobile wireless sensor network,Wireless sensor network,Intrusion detection system,Sensor web | Conference |
ISBN | Citations | PageRank |
978-1-4673-5146-1 | 0 | 0.34 |
References | Authors | |
9 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Michael Riecker | 1 | 23 | 3.44 |
| Ana Barroso | 2 | 1 | 0.68 |
| Matthias Hollick | 3 | 750 | 97.29 |
| Sebastian Biedermann | 4 | 82 | 7.98 |