Abstract
Data-injection attacks on spatial field detection corrupt a subset of measurements to cause erroneous decisions. We consider a centralized decision scheme exploiting spatial field smoothness to overcome lack of knowledge on system parameters such as noise variance. We obtain closed-form expressions for system performance and investigate strategies for an intruder injecting false data in a fraction of the sensors in order to reduce the probability of detection. The problem of determining the most vulnerable subset of sensors is also analyzed.
| Original language | English (US) |
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| Title of host publication | 2016 19th IEEE Statistical Signal Processing Workshop, SSP 2016 |
| Publisher | IEEE Computer Society |
| ISBN (Electronic) | 9781467378024 |
| DOIs | |
| State | Published - Aug 24 2016 |
| Event | 19th IEEE Statistical Signal Processing Workshop, SSP 2016 - Palma de Mallorca, Spain Duration: Jun 25 2016 → Jun 29 2016 |
Publication series
| Name | IEEE Workshop on Statistical Signal Processing Proceedings |
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| Volume | 2016-August |
Other
| Other | 19th IEEE Statistical Signal Processing Workshop, SSP 2016 |
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| Country/Territory | Spain |
| City | Palma de Mallorca |
| Period | 6/25/16 → 6/29/16 |
Bibliographical note
Publisher Copyright:© 2016 IEEE.
Copyright:
Copyright 2017 Elsevier B.V., All rights reserved.
Keywords
- Adversarial detection
- Byzantine sensors
- cyber security
- sensor networks
- spatial field detection