Machine Learning based Trust Computational Model for IoT Services
- Submitting institution
-
Liverpool John Moores University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 1025
- Type
- D - Journal article
- DOI
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10.1109/TSUSC.2018.2839623
- Title of journal
- IEEE Transactions on Sustainable Computing
- Article number
- -
- First page
- 39
- Volume
- 4
- Issue
- 1
- ISSN
- 2377-3782
- Open access status
- Compliant
- Month of publication
- May
- Year of publication
- 2018
- URL
-
-
- 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
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3
- Research group(s)
-
-
- Citation count
- -
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This work is based on the trust concepts in the IoT - Reputation-Experience-Knowledge (REK) trust model produced as a key result of the research sponsored by the co-funded EU-H2020 (Wise-IoT, 723156, €1.5m, 2016-2018) and Trusted Information Infrastructure project (TII – R0190-15-2027, Korean government). The work is the first initiative to apply machine learning algorithms to computational trust areas for reliable IoT service provisioning. The fundamental concepts of trust computation were collated and published by the international standardisation body ITU-T as a flipbook on ‘Trust in ICT’ (https://www.itu.int/en/publications/Documents/tsb/2017-Trust-in-ICT-2017/mobile/index.html) (Reinhard Scholl, deputy director, ITU-T, reinhard.scholl@itu.int).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
