Title
Framework for anticipatory self-protective 5G environments
Date Issued
26 August 2019
Access level
metadata only access
Resource Type
conference paper
Author(s)
Vidal J.M.
Complutense University of Madrid
Publisher(s)
Association for Computing Machinery
Abstract
The forthcoming 5G operational environment entails heterogeneous and multi-dimensional ecosystems where cyber assets, digital actors and cyber-physical risks coexist. In this context, the prediction and anticipation of the attacks propagation thorough the targeted systems promises to be some of the major workhorses of the emerging self-protection capabilities. In the grounds of the Self-Organizing Network (SON) paradigm, it is expected that by taking into account proactive actuations, the decision and enforcement of the best courses of action will be enhanced. With the aim on contributing to their planning and execution, this paper introduces a novel framework for proactive self-protection on 5G environments, the description of an architectural framework able to sustain the rest of the anticipation enablers, the formalization of a knowledge representation and reasoning strategy for active cyber threat mitigation, and a prediction strategy adapted to the difficulties inherent in analyzing events on 5G scenarios. The effectiveness of the proposal has been demonstrated by proof-of-concept instantiation for anticipating the impact of Denial of Service (DoS) attacks on a real communication environment.
Language
English
OCDE Knowledge area
Sistemas de automatización, Sistemas de control
Ingeniería de sistemas y comunicaciones
Subjects
Scopus EID
2-s2.0-85071729131
ISBN of the container
9781450371643
Conference
ACM International Conference Proceeding Series
Sponsor(s)
This Work extends the findings of the project SELFNET: Framework for Self-Organized Network Management in Virtualized and Software Defined Networks, which was funded under the Grant Agreements number H2020-ICT-2014-2/671672 of the European Commission Horizon 2020 Programme. This work is funded by the European Commission Horizon 2020 Programme under grant agreement number 830892, as part of the project H2020-SU-ICT-03-2018/830892 SPARTA: Special projects for advanced research and technology in Europe.
Sources of information:
Directorio de Producción Científica
Scopus