Detection of advanced persistent threat using machine-learning correlation analysis
- Submitting institution
-
De Montfort University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 11011
- Type
- D - Journal article
- DOI
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10.1016/j.future.2018.06.055
- Title of journal
- Future Generation Computer Systems
- Article number
- -
- First page
- 349
- Volume
- 89
- Issue
- -
- ISSN
- 0167-739X
- Open access status
- Technical exception
- Month of publication
- -
- 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
-
6
- Research group(s)
-
-
- Citation count
- 39
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This article is an international collaboration between Universities from the Czech Republic and the UK. It addresses and advances the state-of-the-art in the prediction of cyber-threat Advance Persistent Threats (APT). This system extends our previous publications (e.g. http://hdl.handle.net/2086/17131) that developed algorithms for APT detection, providing correlation and prediction capabilities by using different machine learning algorithms.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -