Transaction propagation delay limits the block interval and is one of the main bottlenecks in improving Bitcoin throughput. However, transaction relay in Bitcoin is entirely voluntary, which results in low bandwidth and high transaction propagation delay. Improving relay motivation by introducing incentives can effectively reduce delay, but it still faces challenges such as Sybil attacks during reward allocation, leakage of network layer privacy, and high on-chain/off-chain overhead. Therefore, this paper proposes Txtail, a practical transaction relay incentive scheme for Bitcoin, based on continuously attaching relay evidence representing the relays’ identity and contribution during transaction propagation. We employ a free pricing mechanism based on the game between relays to allocate rewards fairly. We design an order-insensitive relay evidence structure based on aggregate signatures and public key mapping, which reduces off-chain data overhead while alleviating the leakage of relay paths by obfuscating the relay order. We construct a verifiable lottery mechanism based on Merkle tree commitments to reduce the data that needs to be uploaded to the chain. Both theoretical and experimental results show that Txtail reduces the per-hop off-chain overhead and the overall on-chain overhead by 96.6% and 79.8%, respectively, compared with state-of-the-art baselines, while remaining practical for deployment.

As the artificial intelligence, large model, Metaverse, and Web 3.0 develop rapidly, data is being traded constantly. Existing data exchange methods primarily rely on trusted third parties, which compromises fairness and decentralization. Moreover, existing methods often overlook data access control during trading and typically employ an one-to-one model, resulting in high communication and computational overhead. To address these issues, this article makes the following contributions. First, we propose a blockchain-based secure and fair data trading scheme named fair data trading (FairDT). By leveraging blockchain and smart contracts, FairDT achieves decentralized data trading with high throughput and scalability. Second, we design a fair data exchange mechanism that utilizes commitment schemes, Merkle trees, and other techniques to facilitate dispute resolution with constant on-chain cost when conflicts arise. Third, we incorporate attribute-based encryption to enable fine-grained access control in data trading, thereby reducing the computational burden on data sellers. Finally, we prove that FairDT satisfies access control, fair exchange, completeness, and termination properties. Experimental results on the Ethereum testnet demonstrate that the on-chain cost remains constant, showing that FairDT is highly efficient.

The AI-driven Internet of Things (AIoT) has been widely applied in the field of Internet of Vehicles (IoV) for vehicular cooperation. Federated learning (FL), due to its ability to protect users’ data privacy, reduce communication overhead, and facilitate real-time decision making, is widely applied in the augmented intelligence of things for vehicles (AIoV). However, integrating FL with AIoV poses challenges, including the absence of fine-grained access control, insufficient safeguards for FL tasks and vehicle identities, inadequate security for data transmission, and shortcomings in protecting data storage. These vulnerabilities may lead to risks such as vehicle tracking, model information theft, and data tampering. To address these challenges, we propose a privacy preservation mechanism for AIoV via cloud–edge–vehicle hierarchical sharding blockchain. First, we propose a hierarchical anonymous authentication scheme for IoV devices with stronger scalability and higher fault tolerance. Vehicles only know the attributes of each other or which shard they belong to. Second, we present a secure FL task assignment scheme for AIoV. Edge nodes utilize attribute-based encryption to deploy fine-grained FL tasks based on vehicle attributes. Only users who meet the attributes can decrypt the content, protecting FL tasks content and participant identities. Third, we present a secure data transmission scheme between AIoV devices to protect the identity and data privacy of both parties, while also achieving noninteractive key agreement. Additionally, we propose a scalable secure data sharing and storage scheme based on hierarchical sharding blockchain, aiming to reduce storage overhead and minimize trust costs.

Tor's original design does not have an incentive mechanism but relies on volunteers to maintain their relay nodes for free, eventually leading to the current situation of centralization and lack of relay nodes. Current incentive schemes designed for Tor generally rely on centralized roles, thus presenting a risk of destroying Tor's anonymity. This paper proposes R2E, a decentralized scheme that treats Tor relay services as cryptocurrency mining and rewards the relays with generated tokens while addressing the challenge of how to design decentralized protocols that quantify workload while ensuring fairness and anonymity. We construct the Proof-of-Relay protocol in R2E that enforces random circuit selection, limits the number of nonce attempts, and exploits one-time keys and zero-knowledge proofs to protect participants' identities. We implemented a prototype of R2E based on Ethereum and conducted the trial operation and several confirmation experiments involving$2^{20}$clients,$2^{10}$to$2^{16}$nodes, and 256 circuits for each client to demonstrate its applicability. Analysis and experimental results show that R2E can effectively ensure the anonymity of participants' identities and fairness of incentive allocation while showing good performance in overhead and scalability, making it easy to be quickly applied in practical deployments.

Consensus protocols play a crucial role in determining the security and performance of blockchain systems, with committee-based consensus protocols being particularly important, especially in sharding consensus protocols. Anonymous election of committee nodes can mitigate DDoS attacks and bribery attempts. This approach can also be applied to sharding systems to mitigate the risk associated with a single vulnerable shard. However, current node secret selection schemes still present remaining issues. Single secret leader election schemes struggle to elect multiple leaders with equal anonymity, and existing secret committee election schemes lack adequate measures for tracking malicious nodes. To address these issues, we propose accountable secret committee election schemes that not only regulate the number of nodes but also maintain anonymity during the phases of leader proposal and verifier voting. Furthermore, our schemes enable the tracing of malicious nodes in a threshold way. In addition, we introduce two efficient threshold traceable membership proof schemes for both ad hoc and interactive scenarios. Unlike traceable ring signatures, our scheme can trace malicious nodes even after a single malicious behavior. Subsequently, we apply the accountable secret committee election scheme to sharding blockchains and devise a fully accountable anonymous consensus protocol. The experiment demonstrates that this protocol can elevate the difficulty of corrupting a single shard to the level of compromising the entire system, thereby significantly enhancing the security of the sharding system.

Secret leader election in consensus could protect leaders from Denial of Service (DoS) or bribery attacks, enhancing the blockchain system security. Single Secret Leader Election (SSLE), proposed by Boneh et al., supports electing a single random leader from a group of nodes while the leader’s identity remains secret until he reveals himself. Subsequent research endeavors have introduced distinct approaches to realize SSLE, yet most of these solutions consume relatively high communication complexity. In this paper, we propose an extended SSLE scheme, Secret Multiple Leaders Election (SMLE), based on linkable membership proof. A general SMLE scheme supports the one-time election of multiple consecutive secret leaders while reducing the average communication cost of a single leader election to constant complexity. In particular, SMLE is proven to satisfy a newly proposed consistent unpredictability property for each leader. Specifically, two concrete SMLE constructions are constructed. The first construction is designed for non-interactive scenarios where pre-configured system nodes are not required. The second one is designed for interactive scenarios where nodes operate within a committee. Furthermore, we extend SMLE to Secret Committee Election (SCE) and realize the anonymous node allocation in sharding blockchains utilizing SCE, thereby significantly enhancing the security of the sharding system. Finally, the experimental results indicate that our constructions exhibit minimal communication and computational overhead. When integrated into sharding systems, our protocol could increase an adversary’s attack difficulty, with the enhancement proportion approximately equal to the shard number.