A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf
.
Exploiting Correlations to Detect False Data Injections in Low-Density Wireless Sensor Networks
2019
Proceedings of the 5th on Cyber-Physical System Security Workshop - CPSS '19
We propose a novel framework to detect false data injections in a low-density sensor environment with heterogeneous sensor data. The proposed detection algorithm learns how each sensor's data correlates within the sensor network, and false data is identified by exploiting the anomalies in these correlations. When a large number of sensors measuring homogeneous data are deployed, data correlations in space at a fixed snapshot in time could be used as as basis to detect anomalies. Exploiting
doi:10.1145/3327961.3329530
fatcat:brkqertz7zarhjvblvyeajrohq