The digital transformation brought on by 5G is redefining current models of end-to-end (E2E) connectivity and service reliability to include security-by-design principles necessary to enable 5G to achieve its promise. 5G trustworthiness highlights the importance of embedding security capabilities from the very beginning while the 5G architecture is being defined and standardized. Security requirements need to overlay and permeate through the different layers of 5G systems (physical, network, and application) as well as different parts of an E2E 5G architecture within a risk-management framework that takes into account the evolving security-threats landscape. 5G presents a typical use-case of wireless communication and computer networking convergence, where 5G fundamental building blocks include components such as Software Defined Networks (SDN), Network Functions Virtualization (NFV) and the edge cloud. This convergence extends many of the security challenges and opportunities applicable to SDN/NFV and cloud to 5G networks. Thus, 5G security needs to consider additional security requirements (compared to previous generations) such as SDN controller security, hypervisor security, orchestrator security, cloud security, edge security, etc. At the same time, 5G networks offer security improvement opportunities that should be considered. Here, 5G architectural flexibility, programmability and complexity can be harnessed to improve resilience and reliability. The working group scope fundamentally addresses the following: •5G security considerations need to overlay and permeate through h the different layers of the 5G systems (physical, network, and application) as well as different parts of an E2E 5G architecture including a risk management framework that takes into account the evolving security threats landscape. •5G exemplifies a use-case of heterogeneous access and computer networking convergence, which extends a unique set of security challenges and opportunities (e.g., related to SDN/NFV and edge cloud, etc.) to 5G networks. Similarly, 5G networks by design offer potential security benefits and opportunities through harnessing the architecture flexibility, programmability and complexity to improve its resilience and reliability. •The IEEE FNI security WG s roadmap framework follows a taxonomic structure, differentiating the 5G functional pillars and corresponding cybersecurity risks. As part of cross collaboration, the security working group will also look into the security issues associated with other roadmap working groups within the IEEE Future Network Initiative.

5G core network introduces service based architecture, software defined network, network function virtualization and other new technologies, showing the characteristics of IT and Internet. The new architecture and new technologies not only bring convenience to 5G but also introduce new security threats, especially the unknown security threats caused by unknown vulnerabilities or backdoors. This paper mainly introduces the security threats after the application of software defined network, network function virtualization and other technologies to 5G, summarizes the security solutions proposed by standardization organizations and academia, and puts forward a new idea of building a high-level secure 5G core network based on the endogenous safety and security.

Wearables Security 2022 - As 5G is deployed and applied, a large number of mobile devices have been increasingly deployed on the network. Scenarios such as smartphones, smart car, smart transportation, smart wearable devices, and smart industry are increasingly demanding for networks. And the Internet of Things (IoT), as a new and high technology, will play an important role and generate huge economic benefits. However, IoT security also faces many challenges due to the inherent security vulnerabilities in multiple device interactions and the data also needs more accurate processing. Big data and deep learning have been gradually applied in various industries. Therefore, we have summarized and analyzed the use of big data and deep learning technology to solve the hidden dangers of the IoT security under the consideration of some suggestions and thinking for industry applications.

Network Security Resiliency - The 5G ecosystem is designed as a highly sophisticated and modularized architecture that decouples the radio access network (RAN), the multi-access edge computing (MEC) and the mobile core to enable different and scalable deployments. It leverages modern principles of virtualized network functions, microservices-based service chaining, and cloud-native software stacks. Moreover, it provides built-in security and mechanisms for slicing. Despite all these capabilities, there remain many gaps and opportunities for additional capabilities to support end-toend secure operations for applications across many domains. Although 5G supports mechanisms for network slicing and tunneling, new algorithms and mechanisms that can adapt network slice configurations dynamically to accommodate urgent and mission-critical traffic are needed. Such slices must be secure, interference-aware, and free of side channel attacks. Resilience of the 5G ecosystem itself requires an effective means for observability and (semi-)autonomous self-healing capabilities. To address this plethora of challenges, this paper presents the SECurity and REsiliency TEchniques for Differentiated 5G OPerationS (SECRETED 5G OPS) project, which is investigating fundamental new solutions that center on the zero trust, network slicing, and network augmentation dimensions, which together will achieve secure and differentiated operations in 5G networks. SECRETED 5G OPS solutions are designed to be easily deployable, minimally invasive to the existing infrastructure, not require modifications to user equipment other than possibly firmware upgrades, economically viable, standards compliant, and compliant to regulations.

Network Security Resiliency - The 5G ecosystem is designed as a highly sophisticated and modularized architecture that decouples the radio access network (RAN), the multi-access edge computing (MEC) and the mobile core to enable different and scalable deployments. It leverages modern principles of virtualized network functions, microservices-based service chaining, and cloud-native software stacks. Moreover, it provides built-in security and mechanisms for slicing. Despite all these capabilities, there remain many gaps and opportunities for additional capabilities to support end-toend secure operations for applications across many domains. Although 5G supports mechanisms for network slicing and tunneling, new algorithms and mechanisms that can adapt network slice configurations dynamically to accommodate urgent and mission-critical traffic are needed. Such slices must be secure, interference-aware, and free of side channel attacks. Resilience of the 5G ecosystem itself requires an effective means for observability and (semi-)autonomous self-healing capabilities. To address this plethora of challenges, this paper presents the SECurity and REsiliency TEchniques for Differentiated 5G OPerationS (SECRETED 5G OPS) project, which is investigating fundamental new solutions that center on the zero trust, network slicing, and network augmentation dimensions, which together will achieve secure and differentiated operations in 5G networks. SECRETED 5G OPS solutions are designed to be easily deployable, minimally invasive to the existing infrastructure, not require modifications to user equipment other than possibly firmware upgrades, economically viable, standards compliant, and compliant to regulations.

Network Security Architecture - Software-Defined Networking or SDN (Software-Defined Networking) is a technology for software control and management of the network in order to improve its properties. Unlike classic network management technologies, which are complex and decentralized, SDN technology is a much more flexible and simple system. The new architecture may be vulnerable to several attacks leading to resource depletion and preventing the SDN controller from providing support to legitimate users. One such attack is the Distributed Denial of Service (DDoS), which is on the rise today. We suggest Modified-DDoSNet, a system for detecting DDoS attacks in the SDN environment. A model based on Deep Learning (DL) techniques will be implemented, combining a Recurrent Neural Network (RNN) with an Autoencoder. The proposed model, which was first trained to detect attacks, was implemented in the security architecture of the SDN network, as a new component. The security architecture of the SDN network contains a total of 13 components, each of which represents an individual part of the architecture, where the first component is the RNN - autoencoder. The model itself, which is the first component, was trained in the CICDDoS2019 dataset. It has high reliability for attack detection, which increases the security of the SDN network architecture.

Network Reconnaissance - Through communication reconnaissance, the code stream of mobile communication cell users is obtained, and the code stream of single user are separated from the mixed code stream, which is vital for the behavior analysis and intelligent management of mobile terminals. In this process, the Cell Radio Network Temporary Identifier (C-RNTD is a specific sign of the user terminal, and is also the key to identify and separate different users code stream. However, there are few related studies on CRNTI and acquisition of code stream. To overcome the problem, the combining method about comprehensive searching of the 4th Generation Mobile Communication Technology (4G) Physical Downlink Control Channel (PDCCH), and interception of Sth Generation Mobile Communication Technology (5G) Physical Random Access Channel (PRACH) is proposed, to obtain the users C-RNTI effectively. According to the corresponding downlink control information (DCI), Physical Downlink Shared Channel (PDSCH) are correctly demodulated, descrambled and decoded to obtain the code stream within it. Finally, the communication reconnaissance receiver is used to carry out a real reconnaissance experiment on the actual 4G/5G\_ mobile communication system. The results, i.e. the obtained C-RNTI and code stream verify the correctness and efficiency of the proposed method. It lays an important technical foundation for the accurate identification and management of mobile communication user terminals.

Network Coding - Unmanned Aerial Vehicles (UAVs) are drawing enormous attention in both commercial and military applications to facilitate dynamic wireless communications and deliver seamless connectivity due to their flexible deployment, inherent line-ofsight (LOS) air-to-ground (A2G) channels, and high mobility. These advantages, however, render UAV-enabled wireless communication systems susceptible to eavesdropping attempts. Hence, there is a strong need to protect the wireless channel through which most of the UAV-enabled applications share data with each other. There exist various error correction techniques such as Low Density Parity Check (LDPC), polar codes that provide safe and reliable data transmission by exploiting the physical layer but require high transmission power. Also, the security gap achieved by these error-correction techniques must be reduced to improve the security level. In this paper, we present deep learning (DL) enabled punctured LDPC codes to provide secure and reliable transmission of data for UAVs through the Additive White Gaussian Noise (AWGN) channel irrespective of the computational power and channel state information (CSI) of the Eavesdropper. Numerical result analysis shows that the proposed scheme reduces the Bit Error Rate (BER) at Bob effectively as compared to Eve and the Signal to Noise Ratio (SNR) per bit value of 3.5 dB is achieved at the maximum threshold value of BER. Also, the security gap is reduced by 47.22 \% as compared to conventional LDPC codes.

Network Coding - With the continuous development of the Internet, artificial intelligence, 5G and other technologies, various issues have started to receive attention, among which the network security issue is now one of the key research directions for relevant research scholars at home and abroad. This paper researches on the basis of traditional Internet technology to establish a security identification system on top of the network physical layer of the Internet, which can effectively identify some security problems on top of the network infrastructure equipment and solve the identified security problems on the physical layer. This experiment is to develop a security identification system, research and development in the network physical level of the Internet, compared with the traditional development of the relevant security identification system in the network layer, the development in the physical layer, can be based on the physical origin of the protection, from the root to solve part of the network security problems, can effectively carry out the identification and solution of network security problems. The experimental results show that the security identification system can identify some basic network security problems very effectively, and the system is developed based on the physical layer of the Internet network, and the protection is carried out from the physical device, and the retransmission symbol error rates of CQ-PNC algorithm and ML algorithm in the experiment are 110 and 102, respectively. The latter has a lower error rate and better protection.

Network Coding - Network Coding (NC) enabled cellular networks can be penetrated by faulty packets that deviates the target nodes from decoding packets received. Even a little amount of pollution can be very quickly spread to remaining packets because of the resource exploitation at intermediary nodes. Numerous methods for protecting against data pollution attacks have been developed in the last few years. Another popular alternative is the Homomorphic Message Authentication Code (HMAC). Hackers can target HMAC by tampering with the end-of-packet tags, known as tag pollution assaults, in order to evade detection. To prevent data pollution and tag pollution assaults, a HMAC-based method can be used using two separate MAC tags. In the 5G wireless communication, small cells and collaborative networks have been extensively investigated. The use of network coding in wireless networks can increase throughput while consuming less power. Strong integrity procedures are essential for a coding environment to combat threats like pollution assaults and take full advantage of network coding. Latency and computation overhead can be reduced while maintaining security by modifying and optimising the existing integrity algorithms. This research focuses on analysing security threats in NC enabled small cells.

Nearest Neighbor Search - The organization formed by the connection established between computers, typically by cable, for the purpose of communicating and transmitting data is known as a network. A computer network is a collection of interconnected computers that allow for the sharing of resources including data, programs, and files. When people think of computer networks, they think of the Internet. In this paper, we proposed the usage of a new technique for the categorization of computer network traffic that is based on deep sparse autoencoders and k-nearest-neighbor (KNN) that has been optimized with Grid Search. The autoencoders took the input data and extracted high-level characteristics from it, then connected those features to the KNN. The KNN was used to divide the characteristics into three distinct kinds of assaults (normal and abnormal). In comparison to other investigations, the proposed approach demonstrated an accuracy of 98.23\% in its results.

Microelectronics Security - The boundaries between the real world and the virtual world are going to be blurred by Metaverse. It is transforming every aspect of humans to seamlessly transition from one virtual world to another. It is connecting the real world with the digital world by integrating emerging tech like 5G, 3d reconstruction, IoT, Artificial intelligence, digital twin, augmented reality (AR), and virtual reality (VR). Metaverse platforms inherit many security \& privacy issues from underlying technologies, and this might impede their wider adoption. Emerging tech is easy to target for cybercriminals as security posture is in its infancy. This work elaborates on current and potential security, and privacy risks in the metaverse and put forth proposals and recommendations to build a trusted ecosystem in a holistic manner.

MANET Privacy - Massive amounts of data are being stored in cyberspace as a result of the expansion of the Internet, IoT, and various networking technologies. The privacy and security are the most essential aspects of a network. This survey analyzed the functions of blockchain in network security. The blockchain-based network security mechanism may be used to increase network security because of its decentralization, tamper-resistance, traceability, high availability, and credibility. This survey offers a review of network security studies and their contributions and limits with a critical comparison analysis based on a complete and comprehensive research of the evolution of Blockchain, architectures, working principle, security, and privacy features. This analysis examines network security applications based on blockchain technology with various networking technologies, such as IoT, Industrial IoT, WSN, MANET, VANET, Vehicular Social Network, In-vehicle networking, mobile networks (5G), and so on. For communication, the majority of these networking technologies were combined with IoT. As a result, in this study, the Internet of Things is considered as the primary network employed in important research as examined in the literature review. As a result, the application of network security utilizing blockchain was examined in this study using IoT. This research presents a comparison based on several network solutions that employ blockchain for network security. Finally, the blockchain application in various networks, as well as its difficulties, are examined.

Intelligent Data and Security - The recent 5G networks aim to provide higher speed, lower latency, and greater capacity; therefore, compared to the previous mobile networks, more advanced and intelligent network security is essential for 5G networks. To detect unknown and evolving 5G network intrusions, this paper presents an artificial intelligence (AI)-based network threat detection system to perform data labeling, data filtering, data preprocessing, and data learning for 5G network flow and security event data. The performance evaluations are first conducted on two well-known datasets-NSL-KDD and CICIDS 2017; then, the practical testing of proposed system is performed in 5G industrial IoT environments. To demonstrate detection against network threats in real 5G environments, this study utilizes the 5G model factory, which is downscaled to a real smart factory that comprises a number of 5G industrial IoT-based devices.

Intelligent Data and Security - The introduction of the study primarily emphasises the significance of utilising block chain technologies with the possibility of privacy and security benefits from the 5G Network. One may state that the study’s primary focus is on all the advantages of adopting block chain technology to safeguard everyone’s access to crucial data by utilizing intelligent contracts to enhance the 5G network security model on information security operations.Our literature evaluation for the study focuses primarily on the advantages advantages of utilizing block chain technology advance data security and privacy, as well as their development and growth. The whole study paper has covered both the benefits and drawbacks of employing the block chain technology. The literature study part of this research article has, on the contrary hand, also studied several approaches and tactics for using the blockchain technology facilities. To fully understand the circumstances in this specific case, a poll was undertaken. It was possible for the researchers to get some real-world data in this specific situation by conducting a survey with 51 randomly selected participants.

Information Centric Networks - The 5G research community is increasingly leveraging the innovative features offered by Information Centric Networking (ICN). However, ICN’s fundamental features, such as in-network caching, make access control enforcement more challenging in an ICN-based 5G deployment. To address this shortcoming, we propose a Blockchain-based Decentralized Authentication Protocol (BDAP) which enables efficient and secure mobile user authentication in an ICN-based 5G network. We show that BDAP is robust against a variety of attacks to which mobile networks and blockchains are particularly vulnerable. Moreover, a preliminary performance analysis suggests that BDAP can reduce the authentication delay compared to the standard 5G authentication protocols.

This paper assesses the impact on the performance that information-theoretic physical layer security (IT-PLS) introduces when integrated into a 5G New Radio (NR) system. For this, we implement a wiretap code for IT-PLS based on a modular coding scheme that uses a universal-hash function in its security layer. The main advantage of this approach lies in its flexible integration into the lower layers of the 5G NR protocol stack without affecting the communication s reliability. Specifically, we use IT-PLS to secure the transmission of downlink control information by integrating an extra pre-coding security layer as part of the physical downlink control channel (PDCCH) procedures, thus not requiring any change of the 3GPP 38 series standard. We conduct experiments using a real-time open-source 5G NR standalone implementation and use software-defined radios for over-the-air transmissions in a controlled laboratory environment. The overhead added by IT-PLS is determined in terms of the latency introduced into the system, which is measured at the physical layer for an end-to-end (E2E) connection between the gNB and the user equipment.

The growing complexity of wireless networks has sparked an upsurge in the use of artificial intelligence (AI) within the telecommunication industry in recent years. In network slicing, a key component of 5G that enables network operators to lease their resources to third-party tenants, AI models may be employed in complex tasks, such as short-term resource reservation (STRR). When AI is used to make complex resource management decisions with financial and service quality implications, it is important that these decisions be understood by a human-in-the-loop. In this paper, we apply state-of-the-art techniques from the field of Explainable AI (XAI) to the problem of STRR. Using real-world data to develop an AI model for STRR, we demonstrate how our XAI methodology can be used to explain the real-time decisions of the model, to reveal trends about the model’s general behaviour, as well as aid in the diagnosis of potential faults during the model’s development. In addition, we quantitatively validate the faithfulness of the explanations across an extensive range of XAI metrics to ensure they remain trustworthy and actionable.

ETSI DECT-2020 New Radio (NR) is a new flexible radio interface targeted to support a broad range of wireless Internet of Things (IoT) applications. Recent reports have shown that DECT-2020 NR achieves good delay performance and it has been shown to fulfill both massive machine-type communications (mMTC) and ultra-reliable low latency communications (URLLC) requirements for 5th generation (5G) networks. A unique aspect of DECT-2020 as a 5G technology is that it is an autonomous wireless mesh network (WMN) protocol where the devices construct and uphold the network independently without the need for base stations or core network architecture. Instead, DECT-2020 NR relies on part of the network devices taking the role of a router to relay data through the network. This makes deployment of a DECT-2020 NR network affordable and extremely easy, but due to the nature of the medium access protocol, the routing responsibility adds an additional energy consumption burden to the nodes, who in the IoT domain are likely to be equipped with a limited battery capacity. In this paper, we analyze by system level simulations the energy consumption of DECT-2020 NR networks with different network sizes and topologies and how the reported low latencies can be upheld given the energy constraints of IoT devices.

The Sixth Generation (6G) is currently under development and it is a planned successor of the Fifth Generation (5G). It is a new wireless communication technology expected to have a greater coverage area, significant fast and a higher data rate. The aim of this paper is to examine the literature on challenges and possible solutions of 6G's security, privacy and trust. It uses the systematic literature review technique by searching five research databases for search engines which are precise keywords like “6G,” “6G Wireless communication,” and “sixth generation”. The latter produced a total of 1856 papers, then the security, privacy and trust issues of the 6G wireless communication were extracted. Two security issues, the artificial intelligence and visible light communication, were apparent. In conclusion, there is a need for new paradigms that will provide a clear 6G security solutions.

Unmanned Aerial Vehicles (UAVs) are drawing enormous attention in both commercial and military applications to facilitate dynamic wireless communications and deliver seamless connectivity due to their flexible deployment, inherent line-of-sight (LOS) air-to-ground (A2G) channels, and high mobility. These advantages, however, render UAV-enabled wireless communication systems susceptible to eavesdropping attempts. Hence, there is a strong need to protect the wireless channel through which most of the UAV-enabled applications share data with each other. There exist various error correction techniques such as Low Density Parity Check (LDPC), polar codes that provide safe and reliable data transmission by exploiting the physical layer but require high transmission power. Also, the security gap achieved by these error-correction techniques must be reduced to improve the security level. In this paper, we present deep learning (DL) enabled punctured LDPC codes to provide secure and reliable transmission of data for UAVs through the Additive White Gaussian Noise (AWGN) channel irrespective of the computational power and channel state information (CSI) of the Eavesdropper. Numerical result analysis shows that the proposed scheme reduces the Bit Error Rate (BER) at Bob effectively as compared to Eve and the Signal to Noise Ratio (SNR) per bit value of 3.5 dB is achieved at the maximum threshold value of BER. Also, the security gap is reduced by 47.22 % as compared to conventional LDPC codes.

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.

In recent years, the need for seamless connectivity has increased across various network platforms with demands coming from industries, home, mobile, transportation and office networks. The 5th generation (5G) network is being deployed to meet such demand of high-speed seamless network device connections. The seamless connectivity 5G provides could be a security threat allowing attacks such as distributed denial of service (DDoS) because attackers might have easy access into the network infrastructure and higher bandwidth to enhance the effects of the attack. The aim of this research is to provide a security solution for 5G technology to DDoS attacks by managing the response to threats posed by DDoS. Deploying a security policy language which is reactive and event-oriented fits into a flexible, efficient, and lightweight security approach. A policy in our language consists of an event whose occurrence triggers a policy rule where one or more actions are taken.

As the voucher for identity, digital certificates and the public key infrastructure (PKI) system have always played a vital role to provide the authentication services. In recent years, with the increase in attacks on traditional centralized PKIs and the extensive deployment of blockchains, researchers have tried to establish blockchain-based secure decentralized PKIs and have made significant progress. Although blockchain enhances security, it brings new problems in scalability due to the inherent limitations of blockchain’s data structure and consensus mechanism, which become much severe for the massive access in the era of 5G and B5G. In this paper, we propose ScalaCert to mitigate the scalability problems of blockchain-based PKIs by utilizing redactable blockchain for "on-cert" revocation. Specifically, we utilize the redactable blockchain to record revocation information directly on the original certificate ("on-cert") and remove additional data structures such as CRL, significantly reducing storage overhead. Moreover, the combination of redactable and consortium blockchains brings a new kind of attack called deception of versions (DoV) attack. To defend against it, we design a random-block-node-check (RBNC) based freshness check mechanism. Security and performance analyses show that ScalaCert has sufficient security and effectively solves the scalability problem of the blockchain-based PKI system.

Confidentiality and integrity security are the key challenges in future 5G networks. To encounter these challenges, various signature and key agreement protocols are being implemented in 5G systems to secure high-speed mobile-to-mobile communication. Many security ciphers such as SNOW 3G, Advanced Encryption Standard (AES), and ZUC are used for 5G security. Among these protocols, the AES algorithm has been shown to achieve higher hardware efficiency and throughput in the literature. In this paper, we implement the AES algorithm on Field Programmable Gate Array (FPGA) and real-time performance factors of the AES algorithm were exploited to best fit the needs and requirements of 5G. In addition, several modifications such as partial pipelining and deep pipelining (partial pipelining with sub-module pipelining) are implemented on Virtex 6 FPGA ML60S board to improve the throughput of the proposed design.