Journal article
Attack-resilient Fusion of Sensor Data with Uncertain Delays
ACM transactions on embedded computing systems, Vol.21(4), pp.1-25
08/23/2022
DOI: 10.1145/3532181
Abstract
Malicious attackers may disrupt the safety of autonomous systems through compromising sensors to feed wrong measurements to the controller. This article proposes attack-resilient sensor fusion that combines local sensor readings and shared sensing information from multiple sources. The method results in higher resilience against sensor attacks through jointly considering sensing noise and uncertain communication delay. To be specific, we first identify the considerable impact of the delay on determining attacked sensors. Second, we present a novel two-dimensional abstract sensor model, where each measurement is augmented as a probabilistic interval based on the convolution of the noise and delay. Third, we propose a fusion algorithm that admits the fused value with highest joint probability distribution of the intervals to tolerate corrupted measurements. Finally, we demonstrate the effectiveness of our method in a vehicle-platoon case study using extensive simulations and testbed experiments.
Details
- Title: Subtitle
- Attack-resilient Fusion of Sensor Data with Uncertain Delays
- Creators
- Yanfeng Chen - Northeastern UniversityTianyu Zhang - Northeastern UniversityFanxin Kong - Syracuse UniversityLin Zhang - Syracuse UniversityQingxu Deng - Northeastern University
- Resource Type
- Journal article
- Publication Details
- ACM transactions on embedded computing systems, Vol.21(4), pp.1-25
- Publisher
- ACM
- DOI
- 10.1145/3532181
- ISSN
- 1539-9087
- eISSN
- 1558-3465
- Language
- English
- Date published
- 08/23/2022
- Academic Unit
- Computer Science
- Record Identifier
- 9984696583902771
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