A Markov Multi-phase Transferable Belief Model for Cyber Situational Awareness
- Submitting institution
-
Brunel University London
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 068-201459-14985
- Type
- D - Journal article
- DOI
-
10.1109/ACCESS.2019.2897923
- Title of journal
- Ieee Access
- Article number
- -
- First page
- 39305
- Volume
- 7
- Issue
- -
- ISSN
- 2169-3536
- Open access status
- Compliant
- Month of publication
- February
- Year of publication
- 2019
- URL
-
https://ieeexplore.ieee.org/document/8636494
- Supplementary information
-
https://doi.org/10.21227/8dt8-gx46
- 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
-
2
- Research group(s)
-
2 - Software, Systems & Security (SSS)
- Citation count
- 3
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The Markov Multi-phase Transferable Belief Model (MM-TBM) is a novel approach for predicting multi-phase Cyber-attacks. MM-TBM extends the Transferable Belief Model to address the multi-phase nature of cyber-attacks to obtain previously indeterminable Cyber Situational Awareness. Smets’ TBM as well as conventional single-phase techniques such as Dempster-Shafer theory are inadequate for handling complex multi-phase fusion problems. This work was funded by the UK MoD/DSTL under grant DSTLX1000048609 as part of their Cyber Network Defence Watchtower project to enhance Computer Network Defence (CND) capability for the UK GOSCC (Global Operations Security Control Centre) and protection of UK CND Critical National Infrastructure.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
