Distributed recursive filtering for stochastic systems under uniform quantizations and deception attacks through sensor networks
- Submitting institution
-
Brunel University London
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 039-175582-5807
- Type
- D - Journal article
- DOI
-
10.1016/j.automatica.2016.12.026
- Title of journal
- Automatica
- Article number
- -
- First page
- 231
- Volume
- 78
- Issue
- April
- ISSN
- 0005-1098
- Open access status
- Compliant
- Month of publication
- January
- Year of publication
- 2017
- URL
-
https://bura.brunel.ac.uk/handle/2438/14341
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
3
- Research group(s)
-
1 - Artificial Intelligence (AI)
- Citation count
- 211
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This is the first paper dealing with a radically new cyber-security problem for information transmissions over sensor networks. It is a substantial extension of the authors’ previous winning paper for the 2018 IET Premium Award entitled “Event-based security control for discrete-time stochastic systems”. This paper has solved two long-standing open problems: the first is how to effectively fusing unreliable data and the second is how to cope with complicated network couplings. Owing to its distinct merits and wide citations, this paper has been listed as both a highly cited paper and a hot paper soon after its publication.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
