Security requirements modelling for virtualized 5G small cell networks

Research on next-generation 5G wireless networks is currently attracting a lot of attention in both academia and industry. While 5G development and standardization activities are still at their early stage, it is widely acknowledged that 5G systems are going to extensively rely on dense small cell deployments, which would exploit infrastructure and network functions virtualization (NFV), and push the network intelligence towards network edges by embracing the concept of mobile edge computing (MEC). As security will be a fundamental enabling factor of small cell as a service (SCaaS) in 5G networks, we present the most prominent threats and vulnerabilities against a broad range of targets. As far as the related work is concerned, to the best of our knowledge, this paper is the first to investigate security challenges at the intersection of SCaaS, NFV, and MEC. It is also the first paper that proposes a set of criteria to facilitate a clear and effective taxonomy of security challenges of main elements of 5G networks. Our analysis can serve as a staring point towards the development of appropriate 5G security solutions. These will have crucial effect on legal and regulatory frameworks as well as on decisions of businesses, governments, and end-users.

The 5G network systems are evolving and have complex network infrastructures. There is a great deal of work in this area focused on meeting the stringent service requirements for the 5G networks. Within this context, security requirements play a critical role as 5G networks can support a range of services such as healthcare services, financial and critical infrastructures. 3GPP and ETSI have been developing security frameworks for 5G networks. Our work in 5G security has been focusing on the design of security architecture and mechanisms enabling dynamic establishment of secure and trusted end to end services as well as development of mechanisms to proactively detect and mitigate security attacks in virtualised network infrastructures. The focus of this paper is on the latter, namely the facilities and mechanisms, and the design of a security architecture providing facilities and mechanisms to detect and mitigate specific security attacks. We have developed and implemented a simplified version of the security architecture using Software Defined Networks (SDN) and Network Function Virtualisation (NFV) technologies. The specific security functions developed in this architecture can be directly integrated into the 5G core network facilities enhancing its security. We describe the design and implementation of the security architecture and demonstrate how it can efficiently mitigate specific types of attacks.

The discovery process of OPC Unified Architecture (OPC-UA) is well defined but lacks flexibility when implemented in large networks. While the standard provides concepts for local and global discovery services, the core assumption is that all clients and servers are aware of the discovery server(s) in the network. This dependency is a barrier for Plug-and-Play installations and is overcome by self announces via the multicast Domain Name System (mDNS), however, this scales badly with an increasing number of network nodes and deployed servers. We propose a discovery approach based on Software-Defined Networking (SDN) and Network Function Virtualization (NFV), that installs a plug-and-play mechanism for global OPC-UA discovery in modern virtualized networks.

In this chapter, we present a comprehensive end-to-end (E2E) network slicing framework for fifth-generation (5G) wireless and core networks and provide our vision on network slicing for beyond 5G (B5G) networks using artificial intelligence (AI) technologies. We first give an introduction on the 5G communication networks by specifying distinct 5G networking characteristics. As the key features of 5G pose challenges on quality-of-service (QoS)-oriented resource provisioning, a new concept of network slicing is presented, based on software-defined networking (SDN) and network function virtualization (NFV) technologies, to enhance the overall resource utilization while guaranteeing QoS isolation among services. We focus on developing specific network slicing solutions for both 5G wireless networks and core networks. In addition, the evolution of B5G networks is discussed in terms of a potential networking paradigm shift with new service key performance indicators (KPIs). To satisfy B5G service requirements, a framework of AI-assisted network slicing lifecycle is developed to automate the slice creation with reduced slice management complexity. A case study is presented to demonstrate the effectiveness of the proposed E2E network slicing solutions.Keywords5G communication networksNetwork slicingWireless networksRadio resource slicingCore networksComputing and transmission resource slicingBeyond 5G networksAI-assisted network slicingQoSE2E delay

5G represents the next major phase of mobile telecommunication systems and network architectures beyond the current 4G standards, aiming at extreme broadband and ultra-robust, low latency connectivity, to enable the programmable connectivity for the Internet of Everything2. Despite the significant debate on the technical specifications and the technological maturity of 5G, which are under discussion in various fora3, 5G is expected to affect positively and significantly several industry sectors ranging from ICT to industry sectors such as car and other manufacturing, health and agriculture in the period up to and beyond 2020. 5G will be driven by the influence of software on network functions, known as Software Defined Networking (SDN) and Network Function Virtualization (NFV). The key concept that underpins SDN is the logical centralization of network control functions by decoupling the control and packet forwarding functionality of the network. NFV complements this vision through the virtualization of these functionalities based on recent advances in general server and enterprise IT virtualization. Considering the technological maturity of the technologies that 5G can leverage on, SDN is the one that is moving faster from development to production. To realize the business potential of SDN/5G, a number of technical issues related to the design and operation of Software Defined Networks need to be addressed. Amongst them, SDN/5G security is one of the key issues, that needs to be addressed comprehensively in order to avoid missing the business opportunities arising from SDN/5G. In this report, we review threats and potential compromises related to the security of SDN/5G networks. More specifically, this report contains a review of the emerging threat landscape of 5G networks with particular focus on Software Defined Networking. It also considers security of NFV and radio network access. To provide a comprehensive account of the emerging threat SDN/5G landscape, this report has identified related network assets and the security threats, challenges and risks arising for these assets. Driven by the identified threats and risks, this report has also reviewed and identified existing security mechanisms and good practices for SDN/5G/NFV, and based on these it has analysed gaps and provided technical, policy and organizational recommendations for proactively enhancing the security of SDN/5G.

It is our great pleasure to welcome you to the 2018 ACM International Workshop on Security in Software Defined Networks & Network Function Virtualization - SDN-NFV Security'18. SDN-NFV Security'18 offers a unique opportunity by bringing together researchers from academic, industry, as well as government agencies to discuss security challenges faced by two emerging networking paradigms, Software-Defined Networking (SDN) and Network Function Virtualization (NFV). SDN-NFV Security'18 solicits the submission of original unpublished ideas in 6-page long papers and 4-page short papers that address the latest practices, experiences, and lessons learned on SDN and NFV security. The call for papers attracted submissions from Europe and the United States. SDN-NFV Security'18 accepted 3 full papers be presented in this workshop, after a rigorous review process (at least 4 reviews for each paper) and discussion phase. In addition, we have invited 8 papers (5 full papers and 3 short papers) from domain experts to be presented in the workshop.

With the emergence of Network Function Virtualization (NFV) and Software-Defined Networks (SDN), Service Function Chaining (SFC) has evolved into a popular paradigm for carrying and fulfilling network services. However, the implementation of Mobile Edge Computing (MEC) in sixth-generation (6G) mobile networks requires efficient resource allocation mechanisms to migrate virtual network functions (VNFs). Deep learning is a promising approach to address this problem. Currently, research on VNF migration mainly focuses on how to migrate a single VNF while ignoring the VNF sharing and concurrent migration. Moreover, most existing VNF migration algorithms are complex, unscalable, and time-inefficient. This paper assumes that each placed VNF can serve multiple SFCs. We focus on selecting the best migration location for concurrently migrating VNF instances based on actual network conditions. First, we formulate the VNF migration problem as an optimization model whose goal is to minimize the end-to-end delay of all influenced SFCs while guaranteeing network load balance after migration. Next, we design a Deep Learning-based Two-Stage Algorithm (DLTSA) to solve the VNF migration problem. Finally, we combine previous experimental data to generate realistic VNF traffic patterns and evaluate the algorithm. Simulation results show that the SFC delay after migration calculated by DLTSA is close to the optimal results and much lower than the benchmarks. In addition, it effectively guarantees the load balancing of the network after migration.

In this era wireless technology gaining more popularity, people prefer wireless communication over wired communication due to mobility, scalability and ease of access. However, the traditional wireless network is complex, vendor dependent and inadequate feasibility to incorporate new services, protocols, and APIs. The rapid growth in wireless network raises many thoughtful challenges for network and telecom operators. On such grounds, Innovation of Software Defined Network (SDN) and network function virtualization (NFV) for mobile network opens a new arena of research. This research article presents future mobile Internet architecture (FMIA) with the integration of twin technologies, SDN and NFV that enable rapid access to Internet services. Moreover, the network manager can control services provided by ISPs through proposed architecture.

5G networks represent a paradigm shift from their 4G predecessors, engineered to cater to the burgeoning demands of densely populated areas and the high data throughput requirements of the Internet of Things (IoT) and smart city infrastructures. Beyond enhancing fundamental network attributes such as reliability, availability, and security, 5G introduces architectural innovations to accommodate these advanced needs. This paper delves into the architectural nuances of 5G, focusing primarily on the Standalone (SA) deployment method, distinguished by its utilization of network slicing. This approach leverages cutting-edge virtual network technologies, including Software-Defined Networking (SDN) and Network Function Virtualization (NFV), to forge virtual network slices tailored to diverse consumer needs. Such customization is imperative for meeting the expansive and varied connectivity demands characteristic of 5G networks.To navigate the complexities of 5G architecture, this study advocates for the adoption of Reference Architectures (RAs), which provide a high-level abstraction framework for dissecting and understanding intricate systems. By proposing a model that outlines the standalone architecture of 5G networks, our research lays the groundwork for evolving this model into a comprehensive RA for 5G. This foundational work is instrumental in equipping system designers with the tools necessary for generalizing systems to manage design and deployment challenges effectively, as well as the heterogeneity inherent in system components. Additionally, our proposed model facilitates the establishment of a common vocabulary, promoting a coherent understanding of component interactions and offering a unified system perspective. Ultimately, this paper contributes a pivotal model that not only enhances our comprehension of 5G network architecture but also paves the way for future advancements in network design and deployment, promising to significantly impact the development of smart cities and IoT ecosystems.Keywords: 5G, 5G architecture, Reference architecture, patterns. Network slicing, Network Function Virtualization, Virtual Network Function.

In this Modern era, Software Defined Network (SDN), Network Function Virtualization (NFV), and cloud computing participating of Fifth Generation (5G) network emergence. This paper presents a robust security scheme to provide fortification against major threats along with user privacy in 5G network, two additional entities are introduced. For mobile users, initial authentication is provided at access points by an inventive Highly Secured Authentication and Handover Mechanism (HS-AOHM) scheme which minimizes handover latency without loss of user privacy. Then the authorized user packets are arrived at dispatcher in which a novel Tree Based Switch Assignment (TBSA) algorithm is incorporated. TBSA mitigates the flow table overloading attack by assigning packets to underloaded switches. In controller, DDoS attack is detected with the assist of entropy analysis. Then the suspicious packets are redirected to scrubbing Virtual Network Function (sVNF) in cloud. In sVNF, suspicious packets are classified into normal packets and malicious packets by using Hybrid Fuzzy with Artificial Neural Network (HF-ANN) classifier based on packet features. Normal packets are allowed to access applications whereas malicious packets are dropped at sVNF. Extensive simulation shows security improvement in 5G network in terms of handover latency, holding time, switch failure rate, detection accuracy, and delay.

In order to meet the traffic demand from diverse next generation wireless network applications and exponentially increasing mobile subscriptions, various 5G network architectures are proposed by leveraging Software Defined Networking (SDN) and Network Function Virtualization (NFV) technologies. Network slicing will be one of the 5G technologies that would support next-generation wireless applications over a shared network infrastructure. However, improper network slicing may lead to either over-provisioning or under-utilization of the underlying network infrastructure resources, especially the 5G core network. Over-provisioning of data plane components such as Serving Gateway (SGW) and Packet Data Network Gateway (PGW) can lead to higher CAPEX and OPEX to mobile operators. In this paper, we propose a novel auto-scaling approach called Bit rate Aware Auto Scaling (BAAS) that maintains a precise UE bit rate requirement in the network slices without over-provisioning of data plane resources.

Software Defined Network (SDN) and Network Function Virtualization (NFV) are attracting the attention of telecom operators. The telecom environment requires a set of Carrier Grade requirements such as high availability, high throughput and low latency. SDN faces challenges to meet the Carrier Grade. Based on the JAIN SLEE component model and the Libfluid OpenFlow driver, this work proposes the CREDENCE SDN controller. Our evaluation shows that CREDENCE controller offers a higher throughput and a lower latency when is compared to ONOS and OpenDayLight.

The increasing demand in Mobile Edge Computing (MEC) networks has led to the emergence of Network Function Virtualization (NFV) technology. Through the virtualization technique, NFV can decouple each Virtual Network Function (VNF) from the hardware and deploy it flexibly in the MEC. Each service request in NFV assembles a Service Function Chain (SFC) by tying different VNFs and processes the traffic in the chained order. How to allocate resources and deploy SFC in MEC to meet Quality of Service (QoS) requirements is an important challenge for NFV. An increase in the number of VNFs with traffic passing one after the other causes high delay in SFC assembly. Also, the demanded resources may change during SFC assembly, which is clearly neglected in existing works. Therefore, high delay and resource demand uncertainty during SFC assembly affect QoS. With this motivation, we solve the SFC deployment problem by Parallelizing VNFs under Resource Demand Uncertainty (PVRDU) in MEC. We use the dependency between VNFs to transform the original SFC into a parallel SFC and then assemble several sub-SFCs based on a Deep Reinforcement Learning (DRL) approach. Meanwhile, PVRDU uses a Markov-based approximation algorithm to handle resource demand uncertainty. We perform extensive trace-driven simulations to verify the effectiveness of the proposed algorithm. The evaluation results of PVRDU are promising in different aspects compared to state-of-the-art methods. Specifically, for the considered scenario, DPC reduced SFC delay by as much as 8.7%.

In future 6G networks, mobile edge computing (MEC) is envisioned to offer integrated computing, communication, and storage services at the network edge, enhancing both computational efficiency and communication quality. However, most existing MEC designs neglect the impact of jamming attacks, especially those from intelligent and adaptive jammers. To fill this important research gap, this paper investigates a jamming-resilient MEC framework that aims to improve communication reliability and reduce system delay under adversarial interference. Leveraging the emerging movable antenna (MA) technology, which allows dynamic adjustment of antenna positions and orientations, we propose a novel MA-assisted anti-jamming MEC architecture. Unlike existing works, our model explicitly considers the movement delay caused by MA, which is critical for practical deployment. We jointly optimize the MA positions at both the user equipment (UE) and the base station (BS), BS transmit beamforming, and task offloading ratios to minimize the total system delay. The resulting optimization problem is non-convex and highly coupled. Thus, we develop an efficient algorithm based on penalty dual decomposition (PDD) and successive convex approximation (SCA). Simulation results demonstrate that the proposed scheme significantly outperforms traditional fixed-position antenna (FPA) baselines in terms of jamming resilience and delay minimization, offering new insights into robust MEC system design for 6G networks.

Multipath algorithms except Equal-Cost Multi-Path(ECMP) which has been widely used in networks are difficult to apply, because multipath provisioning is more complex at cross layers and multipath routing need to get all nodes' information. To address the dilemma, this paper proposes a multipath network virtualization implementation scheme with Software Defined Networking (SDN) and Network Function Virtualization (NFV). In this scheme, SDN schedules network resources in a global view for selecting multiple paths and computing weight of each path, and NFV provides computing and storage resources to split flow, add tag, recover flow, to name a few. This paper also proposes a multipath algorithm for elephant flow with network virtualization. Besides, we build an experimental platform based on OPNFV and SDN, and conduct experiments under this experimental platform. The results show that our proposed algorithm applied on multipath network virtualization experimental platform has superior performance than ECMP applied in networks without virtualization.