Within the 5G Service-Based Architecture (SBA), the prevalent centralized frameworks, particularly those managing public key certificates and Network Function (NF) services, face significant security and privacy vulnerabilities due to their reliance on centralized Certificate Authorities (CAs) and Network Repository Functions (NRFs). This centralization in current 5G standards poses two critical issues. One is the risk of single points of failure associated with CAs and NRFs. The other is a substantial risk of privacy leakage in cross-domain NF access authorization. These issues underscore the demand for decentralized NF management with enhanced security and privacy. However, existing related schemes still suffer from such drawbacks as poor security and privacy, low efficiency, and a lack of automation in the management of NF certificates. In this paper, we propose B5G-NFM, a pioneering Blockchain-based 5G Network Function Management scheme designed to bolster security and privacy. B5G-NFM integrates a blockchain middleware network function, a decentralized protocol for managing NF public key certificates, and a decentralized mechanism for NF service discovery coupled with a privacy-preserving NF access authorization protocol. Our thorough security and performance assessment verifies that B5G-NFM not only meets its security and privacy goals, but also aligns with efficiency demand, marking a substantial progress in strengthening 5G network infrastructure.

The prosperity of blockchain technique has spawned numerous types of cryptocurrencies. However, a secure and privacy-preserving cryptocurrency exchange protocol that can support atomicity and unlinkability, and effectively resist various attacks is still missed in the literature. This paper proposes SPCEX, a secure and privacy-preserving cryptocurrency exchange protocol, which supports atomicity and unlinkability, as well as resists collusion attacks, front-running attacks and Sybil attacks without relying on any trust execution environments (TEEs). SPCEX employs a mixing protocol to conceal trader involvement and preserve their identity privacy. It applies a privacy-preserving comparison algorithm based on an improved homomorphic re-encryption scheme to match buy and sell orders secretly, thus resisting front-running attacks. In addition, we construct atomic transactions with smart contracts to protect tokens of honest traders. A collateral deposit mechanism is employed to deter collusive parties and penalize abnormal behaviors, which discourages collusion attacks and Sybil attacks. We analyze the security and privacy of SPCEX, and formally prove the security of the improved homomorphic re-encryption scheme. Through proof-of-concept implementation, we demonstrate its validity and reliability, and show its advanced performance by comparing it with a cutting-edge scheme.

Privacy preservation is highly expected in the Bitcoin Network. However, only applying pseudonyms cannot completely ensure anonymity/unlinkability between payers and payees. Current approaches mainly depend on a mixer service, which obfuscates payer-payee relationships of transactions. While the mixer service improves transaction privacy, it still suffers from some severe security threats (e.g., DoS attack and collusion attack), and does not support effective and reliable off-chain payment in a parallel mode. In this article, we propose a mixing protocol for the Bitcoin Network based on zero-knowledge proof, called SofitMix. It is the first mixing protocol that can effectively resist both the DoS attack and the collusion attack. It can also support a set of parallel off-chain payments in a reliable way no matter whether some payers abort a transaction. We analyze and prove SofitMix security following the Universal Composability model with regard to fair exchange, unlinkability, collusion-resistance, DoS-resistance and Sybil-resistance. Through a proof-of-concept implementation, we demonstrate its validity and fairness. We also show its advance on off-chain payment reliability and DoS attack resistance, compared to TumbleBit.

Wireless sensor network (WSN) is an indispensible part of Internet of Things that has been applied in many fields to monitor environments and collect data from surroundings. However, WSNs are highly susceptible to attacks due to its unique characteristics: large-scale, self-organization, dynamic topology, and constrained resources. A number of systems have been proposed to effectively detect varieties of attacks in WSNs. However, most previous surveys on WSN attacks focus on detection methods for only one or two types of attacks and lack detailed performance analysis. Additionally, the literature lacks comprehensive studies on security-related data (in short security data) collection in WSNs. In this paper, we first provide an overview of WSNs and classify the attacks in WSNs based on protocol stack layers. For the purpose of WSN security measurement, we then research attack detection methods of eleven mainstream attacks. We extract security data that play an important role for detecting security anomaly toward security measurement. We further elaborate the advantages and disadvantages of the existing detection methods based on a number of evaluation criteria. Finally, we highlight a number of open problems in this paper field based on our thorough survey and conclude this paper with possible future research directions.

Device-to-Device (D2D) communications have been regarded as an advanced technology for the next generation mobile communication networks and wireless systems (5G). It is essential to secure D2D communication data for resisting malicious attacks. However, secure D2D communications among mobile devices have not been well solved. By paying attention to the important role of trust in securing D2D communications, in this paper, we propose a scheme using either a General Trust (GT) level issued by a core network or a Local Trust (LT) level evaluated by a device or both to control D2D communication data access by applying Attribute-Based Encryption (ABE). This scheme realizes secure data communications among mobile devices under the legacy system model of Long-Term Evolution (LTE). Performance analysis and evaluation demonstrate that the proposed scheme is effective with regard to security, computation complexity, communication cost, flexibility and scalability.