Fuzzy logic with expert judgment to implement an adaptive risk-based access control model for IoT
- Submitting institution
-
University of Derby
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 787014-1
- Type
- D - Journal article
- DOI
-
10.1007/s11036-019-01214-w
- Title of journal
- Mobile Networks and Applications
- Article number
- -
- First page
- 1
- Volume
- 0
- Issue
- -
- ISSN
- 1383-469X
- Open access status
- Technical exception
- Month of publication
- -
- Year of publication
- 2019
- URL
-
https://link.springer.com/article/10.1007/s11036-019-01214-w
- 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)
-
-
- Citation count
- -
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The paper proposes a novel solution to address limitations of current access control approaches that always give the same result in different circumstances. Its key contribution is providing a dynamic and adaptive risk-based access control model for the IoT system, which is significant for healthcare and military applications. The paper is widely accessed with more than 1400 views since publication in 2019. The paper provides new insights, for example by employing smart contracts to monitor access sessions to detect and prevent malicious activities.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
