Privacy-preserving data trading allows data owners to sell data to consumers through a data trading web platform, the data market, without disclosing sensitive information in raw data. It enables legitimate data transmission and aggregation, facilitating large-scale data-driven model training. However, existing differential privacy-based approaches struggle to inject precisely calibrated noise in a trustworthy manner without revealing raw data to a third party, thus making them fail in achieving strong fairness and controllable privacy simultaneously, especially when facing malicious external adversaries or a corrupted data market.

Data has become a critical driver of innovation in artificial intelligence and the evolution of 6G technologies. The explosive growth of data volume accelerates the convergence of cloud and edge computing, while simultaneously posing heightened challenges to data security and privacy. The emerging cloud-edge-device collaborative paradigm enables dynamic and large-scale data circulation across heterogeneous entities, exposing systems to complex threats such as malicious edge nodes and eavesdropping over untrusted communication channels. In response to these issues, we propose EdgeGuard, a secure and decentralized framework for cloud-edge-device data circulation. EdgeGuard is specifically designed for highly dynamic environments and ensures robust data confidentiality, integrity, traceability, and resilience against both malicious external attackers and compromised edge servers. To underpin its cryptographic foundation, we develop two core primitives. Specifically, we introduce an Aggregatable Publicly Verifiable Secret Sharing (APVSS) scheme that enables efficient sharing of field elements while supporting aggregation and public verifiability. Furthermore, we construct AggDKG, a distributed key generation (DKG) protocol. AggDKG achieves public verifiability and bias resistance with an expected total communication cost of${\mathcal {O}}(\kappa n^{3})$effectively overcoming the scalability limitations inherent in traditional complaint-based protocols. Collectively, these components form a comprehensive framework that strengthens secure and efficient data circulation in cloud-edge-device systems. Experimental data show that AggDKG delivers clear performance gains: across all tested scales, its total running time is only about 8%–65% of that of the DKG of Gurkan et al., and at$n=256$, it reduces per-node runtime by approximately 27% compared with the DKG of Gennaro et al. These results highlight EdgeGuard's superior scalability, lower latency, and stronger Byzantine resilience for secure large-scale deployments.

In Web 3.0’s pursuit of a decentralized and user-autonomous network, traditional access control methods, such as central servers and weak decentralized algorithms, are insufficient regarding security, fault tolerance ability, and scalability. To solve this, we first design a decentralized multi-committee attribute-based encryption, X-ABE, to address the weak decentralization and low fault tolerance in Multi-Authority Attribute-Based Encryption (MA-ABE). X-ABE replaces MA-ABE’s fragile attribute authorities with robust attribute committees, each composed of multiple nodes. By developing dual-wrapped shares techniques, we address the increased dimensionality challenge of secret sharing while maintaining only 1 distributed key generation instance. Also, a formal security definition and proof under the partial adaptive model are given using dual system encryption. Second, X-LOCK, an X-ABE based decentralized access control utilizing consensus plus sharding, is proposed for Web 3.0, to achieve full decentralization, consistency, fault tolerance, user autonomy, and scalability. Third, X-ABE-R is proposed for attribute revocation and is demonstrated in X-LOCK-R with sharding blockchain as an immutable revocation ledger. Fourth, a formal definition and comparative analysis of X-ABE’s fault tolerance abilities are demonstrated, covering aspects of liveness and safety, along with the complexity analysis. Fifth, practical evaluations are conducted, demonstrating that while improving fault tolerance, the overhead remains acceptable.

The cloud-edge-end architecture is suitable for many essential scenarios, such as 5 G, the Internet of Things (IoT), and mobile edge computing. Under this architecture, cross-domain and cross-layer data sharing is commonly in need. Considering cross-domain data sharing under the zero-trust model, where each entity does not trust the others, existing solutions have certain problems regarding security, fairness, scalability, and efficiency. Aiming at solving these issues, we conduct the following research. First, a new plaintext checkable encryption scheme is constructed, which can be used on lightweight IoT devices to verify the ciphertext validity sent by a data owner. Second, we propose a new multi-domain cloud-edge-end architecture based on sharding blockchains and design a cross-domain data sharing scheme under the partial trust model to achieve security, scalability, and high performance. Third, a cross-domain data sharing scheme under the zero trust model is further designed, which can ensure the fairness of both parties in data sharing. Fourth, we give a formal security definition and analysis of cross-domain data sharing. Fifth, we conduct a detailed theoretical analysis of the protocol and give an in-depth functional test and performance test, including the throughput and latency of data sharing policy registration and execution.

Sharding technology is crucial to achieve decentralization, scalability, and security simultaneously. However, existing sharding blockchain schemes suffer from high cross-shard transaction processing latency, low parallelism, incomplete cross-shard views of shard members, centralized reconfiguration, high overhead of randomness generation, and lack of formalized protocol design and security proofs. This paper proposes a flexible sharding (FS) blockchain protocol. First, a cross-shard Byzantine fault tolerance (CSBFT) protocol is designed to cut down confirmation delays when processing cross-shard transactions. Second, we utilize multiple parallel CSBFT where each node acts not only as a leader but also as multiple ordinary members to break through the performance bottleneck caused by a leader’s bandwidth and computing power, improving the system parallelism. Third, a cross-shard transaction censorship attack is proposed, and a cross-shard view-change mechanism is designed to defend against it. Fourth, a secure and truly decentralized shard reconfiguration method combining proof-of-work, proof-of-possession, and intra-shard BFT is designed. Fifth, we utilize a formal protocol design method and give strict security proof for each protocol. Finally, we evaluate FS from both theoretical and practical perspectives. FS is proven to have lower communication and computation complexity and achieve considerable performance.