Security has become the primary concern in many telecommunications industries today as risks can have high consequences. Especially, as the core and enable technologies will be associated with 5G network, the confidential information will move at all layers in future wireless systems. Several incidents revealed that the hazard encountered by an infected wireless network, not only affects the security and privacy concerns, but also impedes the complex dynamics of the communications ecosystem. Consequently, the complexity and strength of security attacks have increased in the recent past making the detection or prevention of sabotage a global challenge. From the security and privacy perspectives, this paper presents a comprehensive detail on the core and enabling technologies, which are used to build the 5G security model; network softwarization security, PHY (Physical) layer security and 5G privacy concerns, among others. Additionally, the paper includes discussion on security monitoring and management of 5G networks. This paper also evaluates the related security measures and standards of core 5G technologies by resorting to different standardization bodies and provide a brief overview of 5G standardization security forces. Furthermore, the key projects of international significance, in line with the security concerns of 5G and beyond are also presented. Finally, a future directions and open challenges section has included to encourage future research.

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A Survey on Security and Privacy of 5G Technologies: Potential Solutions, Recent Advancements, and Future Directions

With the explosive growth of Internet of Things devices and massive data produced at the edge of the network, the traditional centralized cloud computing model has come to a bottleneck due to the bandwidth limitation and resources constraint. Therefore, edge computing, which enables storing and processing data at the edge of the network, has emerged as a promising technology in recent years. However, the unique features of edge computing, such as content perception, real-time computing, and parallel processing, has also introduced several new challenges in the field of data security and privacy-preserving, which are also the key concerns of the other prevailing computing paradigms, such as cloud computing, mobile cloud computing, and fog computing. Despites its importance, there still lacks a survey on the recent research advance of data security and privacy-preserving in the field of edge computing. In this paper, we present a comprehensive analysis of the data security and privacy threats, protection technologies, and countermeasures inherent in edge computing. Specifically, we first make an overview of edge computing, including forming factors, definition, architecture, and several essential applications. Next, a detailed analysis of data security and privacy requirements, challenges, and mechanisms in edge computing are presented. Then, the cryptography-based technologies for solving data security and privacy issues are summarized. The state-of-the-art data security and privacy solutions in edge-related paradigms are also surveyed. Finally, we propose several open research directions of data security in the field of edge computing.

Data Security and Privacy-Preserving in Edge Computing Paradigm: Survey and Open Issues

Security and trust issues in Fog computing: A survey

An exhaustive survey on security and privacy issues in Healthcare 4.0

The industrial Internet of Things (IIoT) supports recent developments in data management and information services, as well as services for smart factories. Nowadays, many mature IIoT cloud platforms are available to serve smart factories. However, due to the semicredibility nature of the IIoT cloud platforms, how to achieve secure storage, access control, information update and deletion for smart factory data, as well as the tracking and revocation of malicious users has become an urgent problem. To solve these problems, in this article, a blockchain-enhanced security access control scheme that supports traceability and revocability has been proposed in IIoT for smart factories. The blockchain first performs unified identity authentication, and stores all public keys, user attribute sets, and revocation list. The system administrator then generates system parameters and issues private keys to users. The domain administrator is responsible for formulating domain security and privacy-protection policies, and performing encryption operations. If the attributes meet the access policies and the user's ID is not in the revocation list, they can obtain the intermediate decryption parameters from the edge/cloud servers. Malicious users can be tracked and revoked during all stages if needed, which ensures the system security under the Decisional Bilinear Diffie–Hellman (DBDH) assumption and can resist multiple attacks. The evaluation has shown that the size of the public/private keys is smaller compared to other schemes, and the overhead time is less for public key generation, data encryption, and data decryption stages.

Blockchain-Enhanced Data Sharing With Traceable and Direct Revocation in IIoT

Fog computing as an extension of cloud computing provides computation, storage and application services to end users. Ciphertext-policy attribute-based encryption (CP-ABE) is a well-known cryptographic technology for guaranteeing data confidentiality and fine-grained data access control. It enables data owners to define flexible access policy for data sharing. However, in CP-ABE systems, the problems of the time required to encrypt, decrypt and attribute update are long-standing unsolved in the literature. In this paper, we propose the first access control (CP-ABE) scheme supporting outsourcing capability and attribute update for fog computing. Specifically, the heavy computation operations of encryption and decryption are outsourced to fog nodes, thus the computation operations for data owners to encrypt and users to decrypt are irrelevant to the number of attributes in the access structure and secret keys, respectively. The cost brought by attribute update is efficient in the sense that we only concentrate on the update of the ciphertext associated with the corresponding updated attribute. The security analysis shows that the proposed scheme is secure under the decisional bilinear Diffie–Hellman assumption. The proposed scheme is efficient, and the time of encryption for data owners and decryption for users are small and constant. The computational ability of fog nodes are fully utilizing during the access control, so the tiny computing cost is left to end users with resource-constrained devices.

An efficient access control scheme with outsourcing capability and attribute update for fog computing

Verifiable keyword search for secure big data-based mobile healthcare networks with fine-grained authorization control

Ciphertext policy attribute-based encryption supporting unbounded attribute space from R-LWE

Aiming to reduce the user's computational overhead and tackle the attribute revocation issue, an attribute-based encryption scheme supporting decryption outsourcing and attribute revocation is proposed in this paper. The proposed scheme outsources some decryption computational tasks to a cloud server such that the computational overhead on the user is simple and constant. We also propose an efficient attribute revocation method which concentrates on the update of the ciphertexts and users' secret keys associated with the corresponding revoked attributes. Moreover, the security analysis indicates that the proposed scheme can resist collusion attacks, and ensure forward and backward secrecy. Experiment results show that our scheme is more efficient compared with other scheme in the literature.

Zehong Chen

Papers

An efficient access control scheme with outsourcing capability and attribute update for fog computing

Verifiable keyword search for secure big data-based mobile healthcare networks with fine-grained authorization control

Ciphertext policy attribute-based encryption supporting unbounded attribute space from R-LWE

Attribute-Based Encryption Scheme Supporting Decryption Outsourcing and Attribute Revocation in Cloud Storage

Multi-user Boolean searchable encryption supporting fast ranking in mobile clouds