Towards the transversal detection of DDoS network attacks in 5G multi-tenant overlay networks
ORCID Identifiers
Document Type
Article
Source of Publication
Computers and Security
Publication Date
11-1-2018
Abstract
© 2018 Elsevier Ltd Currently, there is no any effective security solution which can detect cyber-attacks against 5G networks where multitenancy and user mobility are some unique characteristics that impose significant challenges over such security solutions. This paper focuses on addressing a transversal detection system to be able to protect at the same time, infrastructures, tenants and 5G users in both edge and core network segments of the 5G multi-tenant infrastructures. A novel approach which significantly extends the capabilities of a commonly used IDS, to accurately identify attacking nodes in a 5G network, regardless of multiple network traffic encapsulations, has been proposed in this paper. The proposed approach is suitable to be deployed in almost all 5G network segments including the Mobile Edge Computing. Both architectural design and data models are described in this contribution. Empirical experiments have been carried out a realistic 5G multi-tenant infrastructures to intensively validate the design of the proposed approach regarding scalability and flexibility.
DOI Link
ISSN
Publisher
Elsevier Ltd
Volume
79
First Page
132
Last Page
147
Disciplines
Computer Sciences
Keywords
5G network, DDoS attack, Intrusion detection system, Multi-tenant, Security
Scopus ID
Recommended Citation
Serrano Mamolar, Ana; Pervez, Zeeshan; Alcaraz Calero, Jose M.; and Khattak, Asad Masood, "Towards the transversal detection of DDoS network attacks in 5G multi-tenant overlay networks" (2018). All Works. 3750.
https://zuscholars.zu.ac.ae/works/3750
Indexed in Scopus
yes
Open Access
yes
Open Access Type
Green: A manuscript of this publication is openly available in a repository