A Basic Probability Assignment Methodology for Unsupervised Wireless Intrusion Detection
- Submitting institution
-
The University of Bradford
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 35
- Type
- D - Journal article
- DOI
-
10.1109/ACCESS.2018.2855078
- Title of journal
- IEEE Access
- Article number
- -
- First page
- 40008
- Volume
- 6
- Issue
- -
- ISSN
- 2169-3536
- Open access status
- Compliant
- Month of publication
- -
- Year of publication
- 2018
- URL
-
https://ieeexplore.ieee.org/document/8409949
- 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
-
5
- Research group(s)
-
-
- Citation count
- 4
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This work has an immediate impact on advancing the state-of-the-art in Intrusion Detection Systems (IDSs) and producing solutions for the detection of wireless injection attacks. This paper is significant because it is one of the outcomes of an international collaboration between two research teams in two leading universities in the UK and Asia. Furthermore, the generated datasets, which have the real network traffic of different types of wireless injection attacks, have been made publicly available, including the ground truth. Thus, many researchers in the community have already used and benefited from these datasets.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
