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Authors: Adriana Fernandez-Fernandez, Estefania Coronado, Shuaib Siddiqui – i2CAT; Alberto Erspamer, Georgios Samaras, Vasileios Theodorou – INTRACOM Telecom
Abstract: Mobile networks are facing an unprecedented demand for high-speed connectivity originating from novel mobile applications and services and, in general, from the adoption curve of mobile devices. However, coping with the service requirements imposed by current and future applications and services is very difficult since mobile networks are becoming progressively more heterogeneous and more complex. In this context, a promising approach is the adoption of novel network automation solutions and, in particular, of zero-touch management techniques. In this work, we refer to zero-touch management as a fully autonomous network management solution with human oversight. This survey sits at the crossroad between zero-touch management and mobile and wireless network research, effectively bridging a gap in terms of literature review between the two domains. In this paper, we first provide a taxonomy of network management solutions. We then discuss the relevant state-of-the-art on autonomous mobile networks. The concept of zero-touch management and the associated standardization efforts are then introduced. The survey continues with a review of the most important technological enablers for zero-touch management. The network automation solutions from the RAN to the core network, including end-to end aspects such as security, are then surveyed. Finally, we close this article with the current challenges and research directions.
machine learning models with decentralized data while preserving its privacy by design. This work investigates the possibilities enabled by federated learning concerning IoT malware detection and studies security issues inherent to this new learning paradigm. In this context, a framework that uses federated learning to detect malware affecting IoT devices is presented. N-BaIoT, a dataset modeling network traffic of several real IoT devices while affected by malware, has been used to evaluate the proposed framework.
As an additional contribution and to measure the robustness of the federated approach, an adversarial setup with several malicious participants poisoning the federated model has been considered. The baseline model aggregation averaging step used in most federated learning algorithms appears highly vulnerable to different attacks, even with a single adversary. The performance of other model aggregation functions acting as countermeasures is thus evaluated under the same attack scenarios. These functions provide a significant improvement against malicious participants, but more efforts are still needed to make federated approaches robust.
machine learning models with decentralized data while preserving its privacy by design. This work investigates the possibilities enabled by federated learning concerning IoT malware detection and studies security issues inherent to this new learning paradigm. In this context, a framework that uses federated learning to detect malware affecting IoT devices is presented. N-BaIoT, a dataset modeling network traffic of several real IoT devices while affected by malware, has been used to evaluate the proposed framework.
As an additional contribution and to measure the robustness of the federated approach, an adversarial setup with several malicious participants poisoning the federated model has been considered. The baseline model aggregation averaging step used in most federated learning algorithms appears highly vulnerable to different attacks, even with a single adversary. The performance of other model aggregation functions acting as countermeasures is thus evaluated under the same attack scenarios. These functions provide a significant improvement against malicious participants, but more efforts are still needed to make federated approaches robust.
In this paper, we present a 5GZORRO approach to dynamic cross-CSP slice scaling. Our approach both enables CSPs to collaborate, providing security, and trust with smart multi-party contracts, and facilitates thus achieved collaboration to enable resource sharing across multiple administrative domains, either during slice establishment or when already existing slice needs to expand or shrink. Our approach allows automating both business and technical processes involved in dynamic lifecycle management of cross-CSP network slices, following ETSI’s Zero-Touch Network and Service Management (ZSM) closed-loop architecture, and relying on resource-sharing Marketplace, Distributed Ledger (DL), and Operational Data Lake. We show how this approach is realized in truly Cloud Naive way, with Kubernetes as both business and technical cross-domain orchestrator. We then showcase applicability of the proposed solution for dynamic scaling of Content Delivery Network (CDN) service.
This paper was published in: IEEE 7th International Conference on Network Softwarization (NetSoft) (28 June-2 July 2021)
Date Added to IEEE Xplore: 26 July 2021
DOI: 10.1109/NetSoft51509.2021.9492716
Regarding 5GZORRO, the ability to trade 5G resources (including radio and spectrum ones) across different domains enlarges the set of network resources and extends it to abstractions like services and slices, opening the door to a richer 5G business ecosystem. The 5GZORRO Marketplace leverages the use of DLT and Smart Contracts technologies to enable the trade of 5G resources.
Europe is investing significant resources in research and technology development of 5G networks through the 5G Private Public Partnership (5G PPP). In addition to various scientific and technological topics, the effort focuses on societal and business challenges creating value with 5G networks. This white paper discusses 5G ecosystems as a prerequisite for value creation for and by the engaged stakeholders and return of investment as a potential award for the engagement.
A clear identification of 5G stakeholders supports the creation and evolution of the 5G ecosystems by characterising the potential role that each actor can assume. The identified stakeholder groups include 5G industry and research organisations, vertical sectors’ firms, complementor firms, as well as organisations and associations of providers and consumers active in the value network representing the interests of a larger collection of firms and organisations. Those stakeholder groups include both small and medium enterprises (SME) and larger companies, and whenever relevant academic institutions. In addition, standards organisations, open-source organisation and policy makers are an inherent part of the 5G ecosystems, as are governmental agencies at regional, national and European level that support the creation of value in the 5G ecosystems though funding or procurement of innovations.
Related Info: paper can be read here
Authors: Sergi Figuerola, Eunice Ribeiro – i2CAT
Distributed Trust & Security
