MARINE: Man-in-the-middle attack resistant trust model in connected vehicles
- Submitting institution
-
University of Derby
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 785317-3
- Type
- D - Journal article
- DOI
-
10.1109/JIOT.2020.2967568
- Title of journal
- IEEE Internet of Things
- Article number
- -
- First page
- 3310
- Volume
- 7
- Issue
- 4
- ISSN
- 2327-4662
- Open access status
- Compliant
- Month of publication
- -
- Year of publication
- 2020
- URL
-
https://ieeexplore.ieee.org/document/8962285
- 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)
-
-
- Citation count
- 9
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- A novel trust model in connected vehicles network is proposed. The proposed trust system identifies dishonest nodes performing MiTM attacks in an efficient way as well as revokes their credentials. Extensive simulations are carried out to evaluate the performance and accuracy of MARINE rigorously across three MiTM attacker models and the benchmarked trust model. The simulation results show that for a network containing 35% of MiTM attackers, MARINE outperforms the state-of-the-art trust model by 15%, 18%, and 17% improvements in precision, recall, and F-score, respectively.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
