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DER VERLAG IST IN DER ZEIT VOM 12.06.2019 BIS 23.06.2019 AUSCHLIESSLICH PER EMAIL ERREICHBAR.
aktualisiert am 13. Juni 2019
978-3-8439-2198-5, Reihe Informatik
Denise Miriam Dudek
Lightweight Anomaly Detection for Wireless Sensor Networks
297 Seiten, Dissertation Karlsruher Institut für Technologie (2014), Softcover, A5
For the first time, wireless sensor networks are on the brink of becoming part of everyday life. With growing relevance, security risks associated with pervasively communicating devices are also increasing. To counter these security threats, both cryptographic and non-cryptographic security measures must be applied in cooperation with each other. Security threats that cannot be counteracted with cryptographic means are usually accompanied by specific, measurable changes in networking characteristics such as signal strength, message loss, etc. This work explores the possibility to detect network traffic anomalies using a lightweight statistical model. It allows the sensor nodes in the network to locally observe and learn typical networking characteristics. Deviations from the expected behaviour are detected and classified as anomalous.