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In the current 5th Generation (5G) networking paradigm, the enforcement of Service Level Agreements (SLAs) is a non-trivial measure to ensure the scope and the quality of services and standards between tenants and service providers (SPs). On top of this, Secure Service Level Agreements (SSLA) are introduced to ensure that SPs deliver the most critical and required security-related standards defined in the contract, such as integrity, confidentiality, availability, non-repudiation, and privacy assurance. However, with the tendency for more distributed and multi-stakeholder networking architectures in next-generation networks, the management process of such SSLAs will be challenging due to the diversified security vulnerabilities and complexity of underlying technologies. Although blockchain is emerging as a platform to facilitate such distributed SSLA/SLA management frameworks, its currently available consensus mechanisms are more generic. Still, they need to improve in terms of applying in multi-stakeholder networks. Therefore, this paper presents a novel consensus mechanism called Proof-of-Monitoring (PoM) for a blockchain-based novel SSLA management framework. Moreover, we provide details about the prototype implementation of our proposed consensus algorithm and SSLA management framework. It is proven by comparing our proposal with the other existing solutions that our solution outperforms in many aspects, such as energy consumption, computation cost, and security features.

As a distributed ledger technology, blockchain has received significant attention in revolutionizing telecommunication and networking domains. This article proposes a blockchain-based network slice brokering mechanism for multioperator and multitenant environments of the envisioned 6G networks.

The novel concept of factory-as-a-service (FaaS) allows the agility of adapting the manufacturing process by identifying the industry’s supply chain and user requirements. To cater to FaaS, flexibility in networking and cloud services is a must. 5G network slice broker (NSB) is a third-party mediator that caters to networking resource demand from clients to the service providers. Thus, this article introduces a secure blockchain-based NSB to facilitate FaaS. The proposed secure NSB (SNSB) provides secure, cognitive, and distributed network services for resource allocation and security service level agreement (SSLA) formation with coordination of slice managers and SSLA managers. In SNSB, we introduce a federated slice selection algorithm with Stackelberg game model and reinforcement learning algorithm to compute the real time and the optimal unit price and demand level. We provide an extensive implementation and performance evaluation of SNSB using the slice manager and a custom SSLA manager.

The current evolution of industrial systems is characterized by expectations of increased production efficiency, data security, regulatory compliance, scalability, and environmental sustainability. One of the key technologies driving these advancements is the Industrial Internet of Things (IIoT), together with 5th Generation(5G) and beyond networks. These enable seamless connectivity between infrastructure, machines, and people, facilitating rapid data exchange, automation, monitoring, and control of industrial systems. In this thesis, the main contributions are threefold. First, the thesis proposes a novel decentralized service architecture to establish confidentiality, integrity, and authentication of cloud-integrated IIoT. Secondly, the research proposed a decentralized architecture incorporating Game Theory for efficient and secured network slice brokering and service-level agreement establishment. Finally, the thesis proposed a novel consensus mechanism for reliable IIoT data formulation. This thesis proposes to utilise reputation score as a numerical indicator for the IIoT data reliability in combination with BulletProof zero-knowledge proof to defend the data formulation IIoT from slowly adaptive adversaries to yield energy efficiency. Identifying the scalability limitations in the centralized security services, the thesis incorporated blockchain-based smart contracts as a decentralized service enabler that provides decentralization, lower latency, and transparency with cryptographically integrity-preserved ledger. The proposed service architecture was implemented and evaluated with numerical and programmatic simulations. The thesis results were derived from the comparisons of partial implementations from state-of-art to distinguish the numerical advantages of the proposal. The proposed architecture has yielded significant efficiency improvements, including storage utilization (to 20% in IIoT authentication), latency (Up to 55% in IIoT authentication, Tiivistelmä Teollisten järjestelmien nykykehitykselle on ominaista odotukset tuotannon tehostamisesta, tietoturvasta, säännösten noudattamisesta, skaalautuvuudesta ja ympäristön kestävyydestä. Yksi tähän kehitykseen johtavista keskeisistä teknologioista on teollinen esineiden internet (IIoT) yhdessä viidennen sukupolven (5G) ja muiden verkkojen kanssa. Ne mahdollistavat saumattoman yhteyden infrastruktuurin, koneiden ja ihmisten välillä, mikä helpottaa nopeaa tiedonvaihtoa, automaatiota, valvontaa ja teollisten järjestelmien hallintaa. Tämän väitöstutkimuksen tärkeimmät tulokset ovat kolmella alueella. Ensinnäkin työssä ehdotetaan uutta hajautettua palveluarkkitehtuuria pilvilaskentaan integroidun IIoT:n luottamuksellisuuden, eheyden ja todentamisen varmistamiseksi. Toiseksi tutkimuksessa ehdotetaan hajautettua arkkitehtuuria, joka hyödyntää peliteoriaa tehokkaan ja suojatun verkon viipaloinnin välitys- ja palvelutasosopimuksen toteuttamiseksi. Lopuksi työssä ehdotetaan uutta konsensusmekanismia luotettavaa IIoT-tietojen laatimista varten. Tässä tutkimuksessa ehdotetaan mainepisteiden hyödyntämistä numeerisena indikaattorina IIoT-tietojen luotettavuudelle yhdessä BulletProof-tietokannan kanssa, joka puolustaa datan luomista IIoT järjestelmissä hitaasti mukautuvilta hyökkäyksiltä, energiatehokkuuden huomioiden. Keskitettyjen turvallisuuspalvelujen skaalautuvuusrajoitukset huomioiden, lohkoketjupohjaiset älykkäät sopimukset sopivat hajautetuksi palvelun mahdollistajaksi, joka tarjoaa hajauttamisen, pienemmän viiveen ja läpinäkyvyyden kryptografisesti eheyden säilyttävällä tilikirjalla. Ehdotettu palveluarkkitehtuuri toteutettiin ja arvioitiin numeerisilla ja ohjelmallisilla simulaatioilla. Väitöstutkimuksen tulokset on johdettu vertaamalla osatoteutusta uusinta tekniikkaa erottamaan ehdotuksen numeeriset edut. Ehdotettu arkkitehtuuri on tuottanut merkittäviä tehokkuusparannuksia, joita ovat muun muassa tallennuksen käyttö (20 prosenttiin IIoT-todennuksessa), viive (55

The metaverse, which consists of several universes called verses, is predicted to be the Internet of the future. Recently, this idea has received a lot of discussions, but not enough attention has been paid to the security concerns of these virtual worlds. Primarily when the user and platform server communicate with each other and share sensitive information using the public channel, any attacker can capture the message and can perform various types of attacks such as privacy attack, violation of perfect forward secrecy, impersonation attack, ephemeral secret leakage attack and traceability attack. Therefore, there is impelling need to design an authentication protocol for the metaverse environment that can secure the communication between the user and the platform server. Taking this into account, we designed a zero-knowledge proof authentication protocol based on blockchain for the metaverse environment. The security of the designed protocol is verified through the Burrows-Abadi-Needham (BAN) logic, Scyther tool, and Automated Validation of Internet Security Protocols and Applications (AVISPA) tool. The outcome of the security verification demonstrates that the designed metaverse authentication protocol mitigates all the attacks mentioned above. Moreover, we evaluated the performance of the designed metaverse authentication protocol in terms of computational, communication, storage costs, and energy consumption and compared it with existing metaverse authentication protocols, showing good results taking into account the additional security strength.

Open RAN (ORAN, O-RAN) represents a novel industry-level standard for RAN (Radio Access Network), which defines interfaces that support inter-operation between vendors’ equipment and offer network flexibility at a lower cost. Open RAN integrates the benefits and advancements of network softwarization and Artificial Intelligence to enhance the operation of RAN devices and operations. Open RAN offers new possibilities so different stakeholders can develop the RAN solution in this open ecosystem. However, the benefits of Open RAN bring new security and privacy challenges. As Open RAN offers an entirely different RAN configuration than what exists today, it could lead to severe security and privacy issues if mismanaged, and stakeholders are understandably taking a cautious approach towards the security of Open RAN deployment. In particular, this paper analyzes the security and privacy risks and challenges associated with Open RAN architecture. Then, it discusses possible security and privacy solutions to secure Open RAN architecture and presents relevant security standardization efforts relevant to Open RAN security. Finally, we discuss how Open RAN can be used to deploy more advanced security and privacy solutions in 5G and beyond RAN.

Optimal use of scarce radio spectrum is essential in the proliferation of beyond 5G networks, and promising blockchain technology offers various benefits for the spectrum management. However, existing blockchain-based solutions are expensive, nonoptimized, and lack spectrum fraud detection. This article proposes a novel consensus mechanism for a blockchain-based dynamic spectrum access (DSA) system. The proposed “ Proof-of-Sense ” consensus mechanism operates based on spectrum sensing procedures rather than cryptographic calculations. It is specially designed to address fraudulent/unauthorized access to the spectrum by analyzing the sensed spectrum data. The core of the consensus mechanism is a cryptographic key sharing mechanism inspired by Shamir’s secret sharing scheme. Moreover, the proposed DSA system can enable different microservices, such as automated spectrum auctions, payment and penalty handling, and spectrum fraud detection. A proof of concept based on experimental approaches coupled with Matlab simulations is presented to analyze the performance of the proposed consensus mechanism.

The entire world progression has ceased with the unexpected outbreak of the COVID-19 pandemic, and urges the requirement for contact-less and autonomous services and applications. Realizing these predominantly Internet of Things (IoT) based applications demands a holistic pervasive computing infrastructure. In this paper, we conduct a survey to determine the possible pervasive approaches for utilizing the Multi-Access Edge Computing (MEC) infrastructure in realizing the requirements of emerging IoT applications. We have formalized specific architectural layouts for the considered IoT applications, while specifying network-level requirements to realize such approaches; and conducted a simulation to test the feasibility of proposed MEC approaches.

Network slicing (NS) is technology that enables emerging smart applications and use cases in Fifth Generation (5G) and beyond networks. One such application is smart hospitals, which has diverse network requirements for applications ranging from Augmented Reality (AR) and robot assisted surgeries to connecting large numbers of medical wearables and sensors. NS can be performed in smart hospitals under different strategies based on dynamicity, ownership, and application. This paper investigates how these strategies can be utilized in different smart hospital applications. The performance of each slicing strategy in a hospital network is analyzed under three matrices: bandwidth utilization, handover count, and block count.

Network slicing enables the creation of multiple logical independent networks on physical networking infrastructure. Network slice deployment in a Fifth Generation (5G) mobile network can be classified as vertical and horizontal slicing. The paper compares the performance of the two slicing methods through solving two convex optimization problems, considering several smart hospital scenarios that differ from each other based on their medical speciality. The results are used to draw insights on the most appropriate slicing approach for each setup.

Several symmetric and asymmetric encryption based authentication protocols have been developed for the wireless local area networks (WLANs). However, recent findings reveal that these protocols are either vulnerable to numerous attacks or computationally expensive. Considering the demerits of these protocols and the necessity to provide enhanced security, a lightweight extensible authentication protocol based authentication protocol for WLAN-connected Internet of Things devices is presented. We conduct an informal and formal security analysis to ensure robustness against the attacks. Furthermore, the empirical performance analysis and comparison show that the proposed protocol outperforms its counterparts, reducing computational, communication, storage costs, and energy consumption by up to 99%, 80%, 91.8%, and 98%, respectively. Simulation results of the protocol using the NS3 and its overhead under unknown attacks demonstrate that the proposed protocol performs better in all scenarios. A prototype implementation of the protocol has also been tested to evaluate its feasibility in real-time applications.

The future of networking will be driven by the current emerging trends of combining the physical and virtual realities in cyberspace. Considering the ambient pandemic challenges, the role of virtual and augmented reality will definitely grow over time by transforming into the paradigm of the Metaverse of Things, where each person, thing or other entity will simultaneously exist within multiple synchronized realities. In this paper, we propose a novel framework for future metaverse applications composed of multiple synchronized data flows from multiple operators through multiple wearable devices and with different quality requirements. A new service quality model is proposed based on a customizable utility function for each individual data flow. The proposed approach is based on dynamic fine-grained data flow allocation and service selection using non-fungible tokens, which can be traded over the blockchain among users and operators in a decentralized mobile network environment.

Machine Learning (ML) and Artificial Intelligence (AI) techniques are widely adopted in the telecommunication industry, especially to automate beyond 5G networks. Federated Learning (FL) recently emerged as a distributed ML approach that enables localized model training to keep data decentralized to ensure data privacy. In this paper, we identify the applicability of FL for securing future networks and its limitations due to the vulnerability to poisoning attacks. First, we investigate the shortcomings of state-of-the-art security algorithms for FL and perform an attack to circumvent FoolsGold algorithm, which is known as one of the most promising defense techniques currently available. The attack is launched with the addition of intelligent noise at the poisonous model updates. Then we propose a more sophisticated defense strategy, a threshold-based clustering mechanism to complement FoolsGold. Moreover, we provide a comprehensive analysis of the impact of the attack scenario and the performance of the defense mechanism.

A smart architectural design in 5G with flexibility for various deployment scenarios and service requirements has enabled different business models for mobile network operators in both nationwide and local scales. Future 6G networks will feature even more flexible mobile network deployment driven by spectrum and infrastructure sharing among the operators. In this chapter, we propose a new multi-layer framework for 6G with decoupled operators and infrastructure planes. The proposed framework provides a flexibility of network configuration for multiple operators in condition of open spectrum and infrastructure market by using a multi-dimensional matrix representation of the data flows. In particular, the proposed model supports the dynamic switching of the operator and multi-operator service provision for the end users. As a case study, we have developed an AI-based workflow for the dynamic spectrum allocation among multiple mobile network operators. The key advantage of the proposed workflow is that it can be adjusted to the different combinations of the data flows and thus can be suitable for the spectrum allocation among multiple operators. The intelligent capabilities of the proposed workflow are provided by the deep recurrent neural network based on the long short-term memory architecture. The developed model has been trained over the custom dataset with realistic user mobility in urban area. Simulations results show that the proposed intelligent model provides a stable service quality for end users regardless of the serving operators and outperforms the static and semi-intelligent models.

The growing usage of wireless devices has significantly increased the need for Wireless Local Area Network (WLAN) during the past two decades. However, security (most notably authentication) remains a major roadblock to WLAN adoption. Several authentication protocols exist for verifying a supplicant’s identity who attempts to connect his wireless device to an access point (AP) of an organization’s WLAN. Many of these protocols use the Extensible Authentication Protocol (EAP) framework. These protocols are either vulnerable to attacks such as violation of perfect forward secrecy, replay attack, synchronization attack, privileged insider attack, and identity theft or require high computational and communication costs. In this paper, a lightweight EAP-based authentication protocol for IEEE 802.11 WLAN is proposed that not only addresses the security issues in the existing WLAN authentication protocols but is also cost-effective. The security of the proposed protocol is verified using BAN logic and the Scyther tool. Our analysis shows that the proposed protocol is safe against all the above attacks and attacks defined in RFC-4017. A comparison of the computational and communication costs of the proposed protocol with other existing state-of-the-art protocols shows that the proposed protocol is lightweight than existing solutions.

Multi-Access Edge Computing (MEC) is a cloud computing evolution that delivers end-user services at the mobile network’s edge. As a result, MEC guarantees that users will benefit from ultra-low latency and increased bandwidth when using the services. The orchestration process is the holistic management and control of the edge computing platforms. Handling of service requests forwarded by the MEC subscribers is an inceptive function that requires the intervention of the orchestrator. This paper demonstrates how an advanced service request handler algorithm (MEC-RHA) works on MEC orchestration, considering factors of service priority levels, feasibility, and resource availability when launching a service; while an optimal MEC server selection process is formed based on those factors.

The future of mobile and internet technologies are manifesting advancements beyond the existing scope of science. The concepts of automated driving, augmented-reality, and machine-type-communication are quite sophisticated and require an elevation of the current mobile infrastructure for launching. The fifth-generation (5G) mobile technology serves as the solution, though it lacks a proximate networking infrastructure to satisfy the service guarantees. Multi-access Edge Computing (MEC) envisages such an edge computing platform. In this survey, we are revealing security vulnerabilities of key 5G-based use cases deployed in the MEC context. Probable security flows of each case are specified, while countermeasures are proposed for mitigating them.

Network automation is a necessity in order to meet the unprecedented demand in the future networks and zero touch network architecture is proposed to cater such requirements. Closed-loop and artificial intelligence are key enablers in this proposed architecture in critical elements such as security. Apart from the arising privacy concerns, machine learning models can also face resource limitations. Federated learning is a machine learning-based technique that addresses both privacy and communication efficiency issues. Therefore, we propose a federated learning-based model incorporating the ZSM architecture for network automation. The paper also contains the simulations and results of the proposed multi-stage federated learning model that uses the UNSW-NB15 dataset.

The ever-growing smart applications will expand the Internet of Things (IoT) ecosystem to connect over 75 billion devices by 2025. IoT ecosystems comprise sensors that act as data suppliers and applications where monetary transactions are required to compensate the data producers. This signifies the importance of IoT payments and marketplaces to facilitate micro-transactions of billions of connected devices in the IoT ecosystem, which is heterogeneous, decentralized, and diverse. However, realizing such an ecosystem raises multiple challenges such as overcoming poor inter-operability, resource constraints, and security and privacy vulnerabilities of IoT devices and platforms. Blockchain is a Distributed Ledger Technology (DLT) that can be identified as a potential solution to overcome the challenges in realizing IoT payments and marketplaces. This is due to the characteristics of blockchain such as decentralization, traceability, immutability, and non-repudiation. This paper presents a comprehensive survey on blockchain-based IoT payments and marketplaces. This paper provides a brief introduction to the concepts of IoT payments and IoT marketplaces. Then the technical challenges involved in realizing IoT payment and marketplaces are discussed by highlighting the blockchain-based solutions. Furthermore, blockchain-based smart applications which use IoT marketplace and IoT payment concepts are presented marking the role of blockchain in each of the application. Subsequently, the paper discuss the integration challenges while also highlighting possible solutions. It is envisaged that this paper would shed light on the development of blockchain-based solutions to realize IoT payments and marketplaces.

Industry 5.0 is regarded as the next industrial evolution, its objective is to leverage the creativity of human experts in collaboration with efficient, intelligent and accurate machines, in order to obtain resource-efficient and user-preferred manufacturing solutions compared to Industry 4.0. Numerous promising technologies and applications are expected to assist Industry 5.0 in order to increase production and deliver customized products in a spontaneous manner. To provide a very first discussion of Industry 5.0, in this paper, we aim to provide a survey-based tutorial on potential applications and supporting technologies of Industry 5.0. We first introduce several new concepts and definitions of Industry 5.0 from the perspective of different industry practitioners and researchers. We then elaborately discuss the potential applications of Industry 5.0, such as intelligent healthcare, cloud manufacturing, supply chain management and manufacturing production. Subsequently, we discuss about some supporting technologies for Industry 5.0, such as edge computing, digital twins, collaborative robots, Internet of every things, blockchain, and 6G and beyond networks. Finally, we highlight several research challenges and open issues that should be further developed to realize Industry 5.0.

Recent evolution of the industrial Internet of Things empowers the classical manufacturing model with cloud computing integration for Industry 4.0. Cloud integration advances the capabilities of manufacturing systems with cloud-based controlling and real-time process monitoring, which is renowned as cloud manufacturing (CM). However, cloud integration exposes the entire manufacturing ecosystem to a new set of security risks and increments in end-to-end latency. Moving security services toward the edge eradicates message routing latency toward the cloud and eliminates the central point of failure while leveraging the entire system’s performance. We propose a blockchain and fog-computing-enabled security service architecture that operates on fog nodes at the edge of manufacturing equipment clusters. The proposed service facilitates CM equipment authentication and equipment-cloud channel privacy protection while preserving anonymity and unlinkability over the blockchain. We implemented the proposed architecture with hyperledger fabric and compared the performance advantage over the state-of-the-art solutions.

Multi-access Edge Computing (MEC) is a novel edge computing paradigm that moves cloudbased processing and storage capabilities closer to mobile users by implementing server resources in the access nodes. MEC helps fulfill the stringent requirements of 5G and beyond networks to offer anytimeanywhere connectivity for many devices with ultra-low delay and huge bandwidths. Information-Centric Networking (ICN) is another prominent network technology that builds on a content-centric network architecture to overcome host-centric routing/operation shortcomings and to realize efficient pervasive and ubiquitous networking. It is envisaged to be employed in Future Internet including Beyond 5G (B5G) networks. The consolidation of ICN with MEC technology offers new opportunities to realize that vision and serve advanced use cases. However, various integration challenges are yet to be addressed to enable the wide-scale co-deployment of ICN with MEC in future networks. In this paper, we discuss and elaborate on ICN MEC integration to provide a comprehensive survey with a forward-looking perspective for B5G networks. In that regard, we deduce lessons learned from related works (for both 5G and B5G networks). We present ongoing standardization activities to highlight practical implications of such efforts. Moreover, we render key B5G use cases and highlight the role for ICN MEC integration for addressing their requirements. Finally, we layout research challenges and identify potential research directions. For this last contribution, we also provide a mapping of the latter to ICN integration challenges and use cases.

Based on the collective input of Dagstuhl Seminar (21342), this paper presents a comprehensive discussion on AI methods and capabilities in the context of edge computing, referred as Edge AI. In a nutshell, we envision Edge AI to provide adaptation for data-driven applications, enhance network and radio access, and allow the creation, optimisation, and deployment of distributed AI/ML pipelines with given quality of experience, trust, security and privacy targets. The Edge AI community investigates novel ML methods for the edge computing environment, spanning multiple sub-fields of computer science, engineering and ICT. The goal is to share an envisioned roadmap that can bring together key actors and enablers to further advance the domain of Edge AI.

The latest 5G mobile networks have enabled many exciting Internet of Things (IoT) applications that employ unmanned aerial vehicles (UAVs/drones). The success of most UAV-based IoT applications is heavily dependent on artificial intelligence (AI) technologies, for instance, computer vision and path planning. These AI methods must process data and provide decisions while ensuring low latency and low energy consumption. However, the existing cloud-based AI paradigm finds it difficult to meet these strict UAV requirements. Edge AI, which runs AI on-device or on edge servers close to users, can be suitable for improving UAV-based IoT services. This article provides a comprehensive analysis of the impact of edge AI on key UAV technical aspects (i.e., autonomous navigation, formation control, power management, security and privacy, computer vision, and communication) and applications (i.e., delivery systems, civil infrastructure inspection, precision agriculture, search and rescue (SAR) operations, acting as aerial wireless base stations (BSs), and drone light shows). As guidance for researchers and practitioners, this article also explores UAV-based edge AI implementation challenges, lessons learned, and future research directions.

Faced with the rapid increase in smart Internet-of-Things (IoT) devices and the high demand for new business-oriented services in the fifth-generation (5G) and beyond network, the management of mobile networks is getting complex. Thus, traditional Network Management and Orchestration (MANO) approaches cannot keep up with rapidly evolving application requirements. This challenge has motivated the adoption of the Zero-touch network and Service Management (ZSM) concept to adapt the automation into network services management. By automating network and service management, ZSM offers efficiency to control network resources and enhance network performance visibility. The ultimate target of the ZSM concept is to enable an autonomous network system capable of self-configuration, self-monitoring, self-healing, and self-optimization based on service-level policies and rules without human intervention. Thus, the paper focuses on conducting a comprehensive survey of E2E ZSM architecture and solutions for 5G and beyond networks. The article begins by presenting the fundamental ZSM architecture and its essential components and interfaces. Then, a comprehensive review of the state-of-the-art for key technical areas, i.e., ZSM automation, cross-domain E2E service lifecycle management, and security aspects, are presented. Furthermore, the paper contains a summary of recent standardization efforts and research projects towards the ZSM realization in 5G and beyond networks. Finally, several lessons learned from the literature and open research problems related to ZSM realization are also discussed in this paper.

The next generation of mobile networks, i.e., sixth generation (6G), is expected by 2030, with already burgeoning research efforts towards this goal. Along with various other candidate technologies, blockchain is envisioned to enable and enhance numerous key functionalities of 6G. Thus, the main objective of this paper is threefold: 1) to categorize the different aspects of 6G into four emerging directions that anticipate significant advancements leveraging blockchain, 2) to discuss the potential role of blockchainized 6G under each key emerging direction, 3) to expound on the technical challenges in blockchaining 6G along with possible solutions.

The dawn of smart industries will utilize myriads of interconnected machines, devices, and sensors in factory environments to perform intelligent operations. This paradigm demands satisfying diverse communication requirements through strong network connectivity and services. Network Slicing (NS) in the fifth-generation (5G) and beyond networks is a pragmatic technology that can be utilized to satisfy the communication requirements of smart industries. This paper provides a comprehensive insight on how different NS strategies can be utilized to realize smart industry applications. Furthermore, we simulate a smart factory environment to evaluate the performance of different slicing strategies under two network statistics: band-width utilization and the number of connected clients, along with different base station arrangements.

Several recent works talk about the potential use of network slice brokering mechanism to facilitate the resource allocation of network slicing in next generation networks. This involves network tenants on the one hand and resource/infrastructure providers on the other hand. However, the potential downside of deploying Network Slice Broker (NSB) is that it can be victimized by DoS (Denial of Service) attack. Thus, the aim of this work is three fold. First, to present the possible ways in which DoS/DDoS attacks can be mounted on NSB and their adverse effects. Second, to propose and implement initial blockchain-based solution named as Security Service Blockchain (SSB) to prevent DoS attacks on NSB. Third, to enumerate the challenges and future research directions to effectively utilize blockchain for mitigating DoS/DDoS attacks on NSB. To evaluate the performance the proposed SSB framework is implemented using Hyperledger Fabric. The results manifest that the latency impact of the legitimate slice creation over scaled up malicious traffic remains minimal with the use of SSB framework. The integration of SSB with NSB results in gaining several fold reduction in latency under DoS attack scenario.

Due to the spread of Coronavirus disease 2019 (COVID-19), the world has encountered an ongoing pandemic to date. It is a highly contagious disease. In addition to the vaccination, social distancing and isolation of patients are proven to be one of the commonly used strategies to reduce the spread of disease. For efficient social distancing, contact tracing is a critical requirement in the incubation period of 14-days of the disease to contain any further spread. However, we identify that there is a lack of reliable and practical social interaction tracking methods and prediction methods for the probability of getting the disease. This paper focuses on user tracking and predicting the infection probability based on these social interactions. We first developed an energy-efficient BLE (Bluetooth Low Energy) based social interaction tracking system to achieve this. Then, based on the collected data, we propose an algorithm to predict the possibility of getting the COVID-19. Finally, to show the practicality of our solution, we implemented a prototype with a mobile app and a web monitoring tool for healthcare authorities. In addition to that, to analyze the proposed algorithm’s behaviour, we performed a simulation of the system using a graph-based model.

Although the fifth generation (5G) wireless networks are yet to be fully investigated, the visionaries of the 6th generation (6G) echo systems have already come into the discussion. Therefore, in order to consolidate and solidify the security and privacy in 6G networks, we survey how security may impact the envisioned 6G wireless systems, possible challenges with different 6G technologies, and the potential solutions. We provide our vision on 6G security and security key performance indicators (KPIs) with the tentative threat landscape based on the foreseen 6G network architecture. Moreover, we discuss the security and privacy challenges that may encounter with the available 6G requirements and potential 6G applications. We also give the reader some insights into the standardization efforts and research-level projects relevant to 6G security. In particular, we discuss the security considerations with 6G enabling technologies such as distributed ledger technology (DLT), physical layer security, distributed AI/ML, visible light communication (VLC), THz, and quantum computing. All in all, this work intends to provide enlightening guidance for the subsequent research of 6G security and privacy at this initial phase of vision towards reality.

Internet of Things (IoT) is an emerging technology that makes people’s lives smart by conquering a plethora of diverse application and service areas. In near future, the fifth-generation (5G) wireless networks provide the connectivity for this IoT ecosystem. It has been carefully designed to facilitate the exponential growth in the IoT field. Network slicing is one of the key technologies in the 5G architecture that has the ability to divide the physical network into multiple logical networks (i.e., slices) with different network characteristics. Therefore, network slicing is also a key enabler of realisation of IoT in 5G. Network slicing can satisfy the various networking demands by heterogeneous IoT applications via dedicated slices. In this survey, we present a comprehensive analysis of the exploitation of network slicing in IoT realisation. We discuss network slicing utilisation in different IoT application scenarios, along with the technical challenges that can be solved via network slicing. Furthermore, integration challenges and open research problems related to the network slicing in the IoT realisation are also discussed in this paper. Finally, we discuss the role of other emerging technologies and concepts, such as blockchain and Artificial Intelligence/Machine Learning (AI/ML) in network slicing and IoT integration.

Although the fifth generation wireless networks are yet to be fully investigated, the vision and key elements of the 6th generation (6G) ecosystem have already come into discussion. In order to contribute to these efforts and delineate the security and privacy aspects of 6G networks, we survey how security may impact the envisioned 6G wireless systems with the possible challenges and potential solutions. Especially, we discuss the security and privacy challenges that may emerge with the 6G requirements, novel network architecture, applications and enabling technologies including distributed ledger technologies, physical layer security, distributed artificial intelligence (AI)/ machine learning (ML), Visible Light Communication (VLC), THz bands, and quantum communication.

The emergence of Multi-Access Edge Computing (MEC) technology aims to extend cloud computing capabilities to the edge of the wireless access networks, i.e., closer to the end-users. Thus, MEC-enabled 5G wireless systems are envisaged to offer real-time, low-latency, and high-bandwidth access to the radio network resources. Thus, MEC allows network operators to open up their networks to a wide range of innovative services, thereby giving rise to a brand-new ecosystem and a value chain. Furthermore, MEC as an enabling technology will provide new insights into coherent integration of Internet of Things (IoT) in 5G wireless systems. In this context, this paper expounds the four key technologies, including Network Function Virtualization (NFV), Software Defined Networking (SDN), Network Slicing and Information Centric Networking (ICN), that will propel and intensify the integration of MEC IoT in 5G networks. Moreover, our goal is to provide the close alliance between MEC and these four driving technologies in the 5G IoT context and to identify the open challenges, future directions, and concrete integration paths.

5G is a promising technology that has the potential to support verticals and applications such as Industrial Internet of Things IoT (IIoT), smart cities, autonomous vehicles, remote surgeries, virtual and augmented realities, and so on. These verticals have a diverse set of network connectivity requirements, and it is challenging to deliver customized services for each by using a common 5G infrastructure. Thus, the operation of Local 5G operator (L5GO) networks or private 5G networks are a viable option to tackle this challenge. A L5GO network is a localized small cell network which can offer tailored service delivery. The adaptation of network softwarization in 5G allows vertical owners to deploy and operate L5GO networks. However, the deployment of L5GOs raises various issues related to management of subscribers, roaming users, spectrum, security, and also the infrastructure. This paper proposes a blockchain-based platform to address these issues. The paper introduces a set of blockchain-based modularized functions such as service rating systems, bidding techniques, and selection functions, which can be used to deploy different services for L5GOs. Exploitation of blockchain technology ensures availability, non-reliance on trusted third parties, secure transfer payments, and stands to gain many more advantages. The performance and the viability of the proposed platform are analyzed by using simulations and a prototype implementation.

Local 5G Operator (L5GO) concept is one of the most prominent versatile applications of the 5G in the near future. The popularity of L5GOs will trigger a greater number of roaming and offloading events between mobile operators. However, existing static and the operator-assisted roaming and offloading procedures are inefficient for L5GO ecosystem due to poor service quality, data privacy issues, data transferring delays, excessive costs for intermediary parties and existence of roaming fraud. To address these challenges, we propose a blockchain / Distributed Ledger Technology (DLT) based service platform for L5GOs to facilitate efficient roaming and offload services. As the key contribution, blockchain-based smart contract scheme is proposed to establish dynamic and automated agreements between operators. By using smart contracts, we introduce several novel features such as universal wallet for subscribers, service quality based L5GO rating system, user-initiated roaming process and the roaming fraud prevention system to improve the operational quality of a L5GO. A prototype of the proposed platform is emulated with the Ethereum blockchain platform and Rinkeby Testnet to evaluate the performance and justify the feasibility of the proposal. Upon an extensive evaluation on the prototype, it was observed that the proposed platform offered benefits such as cost effective, more secure and reliable experience.

The ever growing and revolutionizing demands in telecommunication industry to facilitate numerous business verticals are pushing towards more softwarized mobile communication technologies. Utilizing the capabilities of network softwarization, a novel telecommunication concept of local mobile network has been developed. The local mobile networks are getting popular due to their capability of providing efficient and reliable local services to a focused use case with higher flexibility. This paper presents the practical implementation aspects of a softwarized local mobile network and compare its performance with a conventional mobile network and a hybrid network.

The European Telecommunications Standards Institute (ETSI) has introduced the paradigm of Multi-Access Edge Computing (MEC) to enable efficient and fast data processing in mobile networks. Among other technological requirements, security and privacy are significant factors in the realization of MEC deployments. In this paper, we analyse the security and privacy of the MEC system. We introduce a thorough investigation of the identification and the analysis of threat vectors in the ETSI standardized MEC architecture. Furthermore, we analyse the vulnerabilities leading to the identified threat vectors and propose potential security solutions to overcome these vulnerabilities. The privacy issues of MEC are also highlighted, and clear objectives for preserving privacy are defined. Finally, we present future directives to enhance the security and privacy of MEC services.