6533b835fe1ef96bd12a015f
RESEARCH PRODUCT
Defending Surveillance Sensor Networks Against Data-Injection Attacks Via Trusted Nodes
Daniel RomeroRoberto Lopez-valcarcesubject
business.industryComputer scienceDetector020206 networking & telecommunications020207 software engineering02 engineering and technologyAdversaryRobustness (computer science)Injection attacks0202 electrical engineering electronic engineering information engineeringbusinessWireless sensor networkSubspace topologyComputer Science::Cryptography and SecurityComputer networkdescription
By injecting false data through compromised sensors, an adversary can drive the probability of detection in a sensor network-based spatial field surveillance system to arbitrarily low values. As a countermeasure, a small subset of sensors may be secured. Leveraging the theory of Matched Subspace Detection, we propose and evaluate several detectors that add robustness to attacks when such trusted nodes are available. Our results reveal the performance-security tradeoff of these schemes and can be used to determine the number of trusted nodes required for a given performance target.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2018-01-25 |