A hybrid multiobjective RBF-PSO method for mitigating DoS attacks in Named Data Networking
- Submitting institution
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University of East London
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 24
- Type
- D - Journal article
- DOI
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10.1016/j.neucom.2014.11.003
- Title of journal
- Neurocomputing
- Article number
- -
- First page
- 1262
- Volume
- 151
- Issue
- -
- ISSN
- 0925-2312
- Open access status
- Out of scope for open access requirements
- Month of publication
- -
- Year of publication
- 2014
- 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
-
1
- Research group(s)
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1 - Intelligent Systems
- Citation count
- 30
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Named Data Networking (NDN) has been recently proposed to mitigate the inherent limitations in the current IP-based Internet, however it still suffers from new types of DoS attacks that exploit key architectural features of NDN. We developed and designed a new hybrid intelligent system, combining a strong RBF network with PSO and NSGA II optimization algorithms. This system (proactive detection and adaptive reaction) could quickly and effectively respond and mitigate DoS attacks in the adverse conditions. This work was partially supported by projects TIN2013-47272-C2-2 and SGR-2014-881 Catalonia. This contribution is available in named-data.net (ndnsim developers) for learning and further developments.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -