Towards the transversal detection of DDoS network attacks in 5G multi-tenant overlay networks
- Submitting institution
-
University of the West of Scotland
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 13118247
- Type
- D - Journal article
- DOI
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10.1016/j.cose.2018.07.017
- Title of journal
- Computers and Security
- Article number
- -
- First page
- 132
- Volume
- 79
- Issue
- -
- ISSN
- 0167-4048
- Open access status
- Compliant
- Month of publication
- August
- 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
-
3
- Research group(s)
-
-
- Citation count
- 9
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This work addresses transversal detection of cyberattack in 5G multi-tenant infrastructures. It significantly extends the capabilities of a commonly used intrusion detection system, to accurately identify attacking nodes in a 5G network, regardless of multiple network traffic encapsulations. This work is suitable for all 5G network segments including Mobile Edge Computing. Both architectural design and data models are described in this contribution. This work has made significant contribution to security use-case of EU funded SELFNET (SelfOrganized Network Management in Virtualized and Software Defined Networks).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -