Preserving Privacy in the Internet of Connected Vehicles
- Submitting institution
-
University of Newcastle upon Tyne
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 273252-263350-1292
- Type
- D - Journal article
- DOI
-
10.1109/TITS.2020.2964410
- Title of journal
- IEEE Transactions on Intelligent Transportation Systems
- Article number
- n/a
- First page
- -
- Volume
- n/a
- Issue
- -
- ISSN
- 1524-9050
- Open access status
- Not compliant
- Month of publication
- January
- Year of publication
- 2020
- URL
-
https://doi.org/10.1109/TITS.2020.2964410
- 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
-
4
- Research group(s)
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F - Networked and Ubiquitous Systems Engineering (NUSE)
- Citation count
- -
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Sending users' spatio-temporal data to an untrusted edge controller severely exposes users’ privacy. Given the limited computational resources in the vehicles and ITS' evolving nature, developing adaptive privacy-preserving system is extremely challenging. This paper proposed a stringent data privacy preservation mechanism for untrusted distributed edge networks in connected vehicles. Data thresholding and filtering to preserve privacy made the contribution unique and up to the benchmark for scalable system building based on connected vehicle requirements. This paper was published in the leading journal for intelligent transportation systems (Google Scholar).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -