Online ride-hailing services (ORHS) are changing the travel mode. The quality evaluation of ORHS is essential to regulate driver behavior and guide passengers in choosing good services. The existing quality evaluation methods of ORHS rely on subjective passenger feedback, while they are susceptible to malicious or paranoid feedback, resulting in untrustworthy evaluation results. This paper proposes a non-subjective trust mechanism for ORHS to supplement existing evaluation methods. Inspired by the trust machine, this mechanism defines the concept of non-subjective trust to measure the quality of ORHS. It uses trajectory data collected by infrastructure as a parameter to calculate the non-subjective trust value of ORHS, which can ensure the trustworthiness and authenticity of the calculation results. This mechanism also improves the CKKS homomorphic encryption algorithm to ensure both the privacy protection of the trajectory data and the effective calculation of non-subjective trust values. In addition, a blockchain is adopted to store trajectory data cipher text and trust values plaintext in the infrastructure. It promotes its flexible management and use and ensures the security of original data and traceability of evaluation results. Theoretical analysis and experiments show that the trust value calculated by this mechanism is trustworthy, and its time costs are feasible.

The rapid evolution of artificial intelligence (AI) and large language models (LLMs) technologies is fundamentally reshaping the landscape of higher education. As the primary arena for cultivating high-level innovative talents, graduate education faces an urgent imperative to integrate LLMs to enhance teaching quality and research efficiency. This paper focuses on graduate education in cryptography, a field characterized by high abstraction, rapid iteration, and stringent security requirements. Utilizing the world's first LLM in cryptography, the CryptoLLM, we construct a comprehensive data-process-system trinity teaching strategy. We propose a novel teaching model that transitions from traditional knowledge transmission to ability-oriented construction. By leveraging CryptoLLM's capabilities in intelligent algorithm analysis, protocol design, engineering implementation, and dynamic resource generation, this paper aims to promote the intelligent transformation of cryptography graduate education. Furthermore, we address potential risks such as technical dependence and ethical concerns, offering a tiered implementation pathway. This work serves as a theoretical framework and practical reference for nurturing high-level cryptographic talent in the era of generative AI.

Unmanned Aerial Vehicle (UAV) networks are increasingly used in scenarios such as power inspection, agricultural plant protection, and emergency rescue. These scenarios often suffer from a deficiency of robust infrastructure, which can result in decentralized security challenges in UAV identity management. Some blockchain-based schemes have been proposed to construct distributed trust mechanisms that do not rely on centralized infrastructure. However, these schemes have yet to address the security of UAV reconnection and the task integrity protection following disconnections. Moreover, the integration of blockchain technology introduces severe resource overhead, decreasing the operational endurance of UAVs and extending management latency. In this paper, we present a scheme for a distributed UAV network based on blockchain technology to ensure secure identity management. Our scheme includes a secure UAV reconnection protocol, task result backup method, and a lightweight blockchain framework. Specifically, the reconnection protocol employs a hybrid authentication approach that combines intrinsic system characteristics with test task behavior, ensuring both the security of UAV reconnection authentication and the robustness of the UAV cluster. The backup method guarantees the integrity of task results even when any disconnection occurs, by redundantly storing results in both the head UAV and a member UAV. We construct a lightweight blockchain framework by eliminating energy-intensive mining processes and simplifying on-chain operations, thereby reducing resource consumption. We utilize the Universally Composable (UC) security model to prove that our scheme can resist the attacks proposed, and we theoretically analyze the consensus process of our lightweight blockchain, showing that it is more streamlined compared to the mainstream blockchain Fabric. Simulation results demonstrate that our scheme exhibits superior robustness and task integrity. Our scheme reduces the average consensus latency by over 60% compared to the Fabric, and at peak times, it requires only 60% of the CPU utilization compared to Fabric.

Cross-chain techniques improve blockchain scalability and interoperability, providing decentralized exchange and cross-chain collaboration services for Internet of Things (IoT) data across various domains. However, current state-of-the-art (SOTA) solutions for cross-chain data exchange across multiple domains are constrained by synchronous networks, hindering efficient data exchange in intermittent network environments. Furthermore, there is a lack of research on asynchronous cross-chain transaction pool mechanisms, which are crucial for optimizing system utility. In this paper, we propose AC-BaaS, an asynchronous cross-blockchain as a service framework tailored for the multi-domain IoT. Built upon a specially designed asynchronous sidechain architecture, the system leverages a committee to provide AC-BaaS for data exchange across multiple IoT domains. To fulfill the need for asynchronous and efficient data exchange, we combine the ideas of aggregate signatures and verifiable delay functions to devise a novel cryptographic primitive called delayed aggregate signature (DAS), which constructs asynchronous cross-chain proofs (ACPs) that ensure the security of cross-chain interactions. To ensure the consistency of asynchronous transactions, we propose a multilevel buffered transaction pool that guarantees the transaction sequencing. We further propose a heuristic for optimizing the utility of the buffer pool mechanism to strike a balance between performance and resource consumption. We also examine DAS delay size settings to trade-off security and efficiency. We analyze and prove the security of AC-BaaS, simulate asynchronous communication environments under various security levels, and conduct a comprehensive evaluation. The results show that AC-BaaS outperforms SOTA schemes, improving throughput by an average of 1.71 to 5.09 times, reducing transaction latency by 64.36% to 85.49%, and maintaining comparable resource overhead.

Secure data transmission has become the foundation of social trust and economic development. The advent of blockchain has expanded the model of secure data transmission, addressing issues such as the absence of distributed trust and centralized single points of failure. This paper proposes a secure data transmission architecture based on blockchain. Firstly, it summarizes the current research on secure data transmission and lists main driving technologies. Secondly, it refines the architecture from the perspectives of security guarantee, performance optimization, and distributed application. Finally, it provides use cases for the architecture and conducts security analysis and performance evaluation to prove the effectiveness and availability of the architecture.

In distributed large-scale intelligent computing, efficient collaboration between the cloud and edge devices is essential to provide rapid data access for a vast number of users, which is crucial for optimal data storage services. The edge servers are utilized to meet the data access requirements of adjacent group users. Numerous data auditing schemes for cloud computing have been proposed to protect user data integrity and avoid the threat of data leakage, loss, or tampering. However, secure cloud-edge storage of group users remains to be further studied. This paper proposes a novel blockchain-assisted blinded data auditing scheme for cloud-edge systems. Firstly, blockchain technology is utilized to monitor the activities of a semi-trusted third-party auditor (TPA). Secondly, user identifiers are utilized to trace the malicious behaviors in the systems. In addition, a data blinding algorithm is utilized to ensure that the raw data is unavailable to a curious TPA. Both security analysis and performance assessment demonstrate that this scheme conducts data auditing for cloud-edge systems with reliability and efficiency.

As an advanced technology, blockchain is the core of trust establishment, data interaction, and value delivery in a distributed zero-trust environment. However, due to the characteristics of equal autonomy of nodes, multi-party maintenance of data, and closed isolation between chains, the blockchain system faces the problem of impossible triangle. Many researchers have studied blockchain scalability methods. This paper investigates the existing methods from three aspects of the network scalability, throughput scalability, and function scalability. It also compares and summarizes these methods, aiming to direct future research in the scalability optimization of blockchain.

Sidechain techniques improve blockchain scalability and interoperability, providing decentralized exchange and cross-chain collaboration solutions for Internet of Things (IoT) data across various domains. However, current state-of-the-art (SOTA) schemes for IoT multi-domain data exchange are constrained by the need for synchronous networks, hindering efficient cross-chain interactions in discontinuous networks and leading to suboptimal data exchange. In this paper, we propose AsyncSC, a novel asynchronous sidechain construction. It employs a committee to provide Cross-Blockchain as a Service (C-BaaS) for data exchange in multi-domain IoT. To fulfill the need for asynchronous and efficient data exchange, we combine the ideas of aggregate signatures and verifiable delay functions to devise a novel cryptographic primitive called delayed aggregate signature (DAS), which constructs asynchronous cross-chain proofs (ACPs) that ensure the security of cross-chain interactions. To ensure the consistency of asynchronous transactions, we propose a multilevel buffered transaction pool that guarantees the transaction sequencing. We analyze and prove the security of AsyncSC, simulate an asynchronous communication environment, and conduct a comprehensive evaluation. The results show that AsyncSC outperforms SOTA schemes, improving throughput by an average of 1.21 to 3.96 times, reducing transaction latency by 59.76% to 83.61%, and maintaining comparable resource overhead.

As cloud computing gains widespread adoption, cloud storage services have become the primary means of data management for users. Authenticated data structures (ADS) are a novel computational model designed to address data authentication problems in distributed environments. With the growing demand for robust data security, vulnerability detection in storage systems has become a critical area of focus to ensure resilience against potential threats. However, traditional ADS, while ensuring consistency between cloud data and source data, have limitations in handling dynamic data operations on multiple types of files, storage space expansion, and single-point failure issues. To tackle these issues, this paper proposes a blockchain-assisted classifiable data auditing scheme with dynamic operations. First, trapdoor hash functions are used to construct a binary tree. During dynamic data operations, the impact of hash updates is confined to a subset of nodes, ensuring global stability and reducing computational resource consumption. Second, innovative data structures and verification mechanisms are introduced, reducing the risk of single-point failures by decentralizing the dependency on verification paths. Finally, data types are confirmed based on data identifiers, and corresponding path information is recorded, enabling efficient and rapid dynamic operations on specific types of files within multi-source data. Both security analysis and performance assessment demonstrate that BCDAS conducts data auditing with reliability and efficiency.

With the development of artificial intelligence generated content (AIGC), the issue of interest disputes caused by data abuse has become increasingly severe. Recently, data is still dominated by the central organization instead of its producer. It is challenging to guarantee data sovereignty autonomy which helps to reasonably play the value of data and facilitate the controllable evolution of AI. The emerging “read-write-own” based Web3 is a promising pattern to break the data monopoly held by central organizations. In this paper, we propose a data interaction-oriented Web3 architecture driven by blockchain and oracle with the features of data sovereignty autonomy, zero trust, distributed security, and fair payment and incentive to guarantee data sovereignty autonomy. We finally provide a use case on life insurance to implement and evaluate our Web3 architecture in terms of performance.

This paper designs an "institution-business-system" multi-level security sandbox system from the perspective of cross-department data sharing and combined with Fabric blockchain technology. The system makes full use of the characteristics of blockchain technology, such as decentralization, immutable and consensus mechanism, to achieve collaborative services of secure sandbox facilities. Then this paper proposes a distributed and regulated privacy protection scheme that combines group signature, private address protocol, zero-knowledge proof and attribute encryption. This algorithm improves the group manager mechanism of group signature. The experimental results show that the scheme can ensure the data traceability and realize the supervision of both sides of the transaction, and improve the level of privacy protection of data on the chain.

Recent Blockchain-based Internet of Vehicles (BIoV) solutions are proposed to provide the capabilities of trust management and incentive distribution for traffic information interaction in decentralized trustless Internet of Vehicles (IoV). However, existing trust management methods in BIoV are designed based on subjective user feedback, which is vulnerable to bad-mouthing and collusion attacks. Besides, these incentive strategies achieve accurate information interaction based on the game theory, yet it is challenging for the practical IoV scenario without completely explicit parameters. To address these issues, we propose TI-BIoV, a traffic information interaction system based on three blockchains for IoV with the nonsubjective trust evaluation and optimal incentive with partial inexplicit parameters. Specifically, a nonsubjective trust mechanism is designed based on the traffic information offset calculated by other related traffic information, which ensures the change of vehicle trust value without any subjective factors. On this basis, a trust-based consensus protocol, which selects entities with high trust values as participants, is given to realize the reliable public audit of transactions. According to traffic information accuracy measurements, we develop a $Q$ -learning-based algorithm to encourage vehicles continuously submit accurate traffic information and optimally schedule the incentive for both platform and vehicle via training with incompletely explicit parameters of TI-BIoV. Finally, we analyze the security properties and common attacks of TI-BIoV and implement a prototype. The experimental results show that TI-BIoV achieves reliable consensus with nonsubjective trust evaluation and runs stably for a long time with two-sided incentive strategies.

Non-Fungible Tokens (NFTs) do hold the promise of providing Web3 with the opportunity for self-sovereignty of users' physical assets. However, existing NFT marketplaces lack a generic design that allows the value of assets to flow efficiently. In this paper, we propose a generic NFT architecture for Web3. The architecture supports the rapid development of the upper application environment and automated value mapping of the underlying physical asset environment. To connect these two environments, a generic connecter has been designed to provide flexible storage for mapping data management, and to support universal cross-chain transactions. With these features, the values of heterogeneous physical assets can coexist in a unified Web3 world, and rich value transfer services can be developed on demand. This paper discusses the background of the proposed architecture, the open problems and our initial solution, as well as our design principles and advantages, and finally validates this novel NFT architecture.

Prediction on compatibility of a service is crucial because it not only provides assurance for service requesters to successfully fulfil the workflow, but also relieves the pressure of the service pool from overload. Existing researches on parameter prediction mainly rely on collaborative filtering and matrix factorization, which are easily exposed to data-sparse problem, and they don't have solid support from mathematical proof. In this paper, we are the first to propose a method to predict compatibility with reliable mathematical proof, and its mechanism prevents data-sparse. Firstly we propose an architecture called Topology Retrievable Service Oriented Architecture, which is capable of collecting individual invocation records in a specific period of time and generate the whole topology of the service pool. Secondly, based on the architecture we presented, we give our definitions of Link-ability, propose Link-ability Generation Algorithm and present our solid mathematical strategies in the aspect of Markov Process. Lastly, we perform a series of experiment to strengthen our point, the result shows that our Link-ability not only reveals compatibility, but also potential compatibility of connecting services.

Unmanned Aerial Vehicle (UAV) networking is increasingly used in field environments such as power inspection, agricultural plant protection, and emergency rescue. To guarantee UAV networking security, UAV identity authentication attracts wide attention, especially in the field environment without perfect infrastructure. Some blockchain-based UAV identity authentication solutions are proposed to establish decentralized and trusted authentication systems without relying on infrastructure. However, these solutions do not support disconnected UAV reconnection or even disband a cluster directly after its head UAV disconnection, which compromises cluster robustness and task result integrity. In this paper, we propose a blockchain based identity authentication solution oriented to multi-cluster UAV networking with a UAV disconnection mechanism and a task result backup mechanism. Specifically, we build a blockchain maintained by head UAVs of all clusters, managing identity information to guarantee the security of decentralized identity management. The UAV disconnection mechanism permits a verified distributed UAV reconnection to ensure the robustness of the UAV cluster, and on this basis, the task result backup mechanism ensures the integrity of the task results stored in a cluster even any UAV disconnection. Finally, extensive experimental results prove the superiority of our solutions in terms of robustness, integrity, delay, and energy consumption.

The increasing blockchain-based Internet of Vehicles (BIoV) networks attract attention, and there is little cross-chain data interaction solution in this scenario yet. Due to the limited data amount and types, BIoV networks also require off-chain data to provide intelligent services and experiences. Nowadays, lots of surveys concentrate on cross-chain and on-off-chain interoperability for blockchains, while BIoV networks lack a secure and effective interoperability solution to satisfy both cross-chain and on-off-chain interoperability, where ensuring the authenticity of inter-chain semi-authentic data and off-chain inauthentic data is challenging. To solve these challenges, this paper proposes a BIoV interoperability solution driven by a multiple oracle network. Kinds of consensus algorithms implement the voting to ensure the authenticity of verified data against multiple malicious attacks. The voting is implemented by kinds of consensus algorithms to ensure the authenticity of verified data against multiple malicious attacks. Extensive experiments are conducted to prove the effectiveness of this solution in terms of transaction performance and resource occupancy.

With the extensive application of the Internet of Things (IoT), multi-domain IoT appears as the additional coordination and control ability of IoT. However, the emerging multi-domain IoT suffers from some security challenges, such as insider threats and cross-domain data exchange issues. In this paper, we propose a data exchange model for the multi-domain IoT environment driven by blockchain, addressing expensive cross-domain access control and low data exchange throughput issues. At the core of this model is a chaincode-based cross-domain access control scheme and a domain-as-a-shard (DaaS) high parallel throughput optimization technology. In particular, the access control scheme is maintained by multiple blockchain nodes to ensure access control strategy distributed storage and data cross-domain controllability. The data in this model cannot be exchanged across domains until all nodes jointly verify that the access control strategy is valid. Moreover, the throughput optimization technology sets the IoT domain as the blockchain shard to process data exchange in parallel and scale up the throughput dramatically. In each shard, data exchange is processed in the form of the blockchain transaction independently to improve the transaction throughput of our model. Finally, security analysis proves that our model successfully ensures access control strategy non-repudiation and cross-domain data controllability. Extensive experiments on Hyperledger Fabric show that the transaction throughput of our model is nearly three times that of the original Fabric v1.4.

Blockchain-based crowdsourcing solutions have been widely used in the industry to solve insider threats and free-riding/false-reporting issues. However, the existing solutions suffer from three main limitations: 1) inability to concurrently achieve task privacy protection and distributed transparent storage, 2) limited transaction throughput caused by serial transaction processing, and 3) low fault-tolerance ability of their practical byzantine-fault-tolerance (PBFT) consensus protocols. In order to overcome these limitations, this paper proposes a novel hybrid-blockchain crowdsourcing platform named CHChain. The core of CHChain is a hybrid blockchain structure, which achieves distributed and transparent storage while guaranteeing task privacy by isolating the private information of each task (e.g., task response, evaluation, and feedback) into its own private task chain, and recording other common information of tasks (e.g., task ID, reward, and deadline) into a common chain. To improve transaction throughput, we then design a parallel-transaction-processing chaincode (PTPC), a chaincode running on the hybrid blockchain structure, to process transactions in parallel, which is also responsible for evaluating the reputations of platform users. For fault-tolerance enhancement, we finally design a Reputation-based PBFT (R-PBFT) consensus protocol based on the hybrid reputation values of platform users. Extensive experiment results showed that the transaction throughput of CHChain is nearly twice as much as those of the existing solutions. Moreover, the fault tolerance of R-PBFT can be approximately 98%, which is much higher than that of the PBFT, 1/3.

Software Defined Network (SDN) is an essential technology in the next-generation network, while the original SDN architecture with a single controller has a single point of failure and scalability issues. Nowadays, several multi-controller solutions are proposed to address the above issues. However, multiple controllers also bring malicious administrator threats and state consistency issues. Therefore, in this paper, we design a novel blockchain-based SDN architecture, named B-SDN, utilizing the characteristics of non-tamper and non-repudiation. We also re-construct the control layer of the SDN network with the combination of horizontal and vertical architecture. Finally, extensive experiments are conducted to evaluate the throughput, latency, memory usage, CPU usage, network traffic of the proposed architecture.

In recent years, more and more Internet of Things (IoT) applications are emerging to make our daily life smarter. However, these IoT applications are developed in an isolated vertical architecture and suitable for a specific scene or environment. In other words, they do not exchange and reuse data between each other, resulting in the issue of IoT application isolations. To address this problem, we propose a cross-domain data sharing mechanism named MicrothingsChain, which allows the exchange and reuse of data among various applications in a collaborative way. This paradigm calls for novel security and access control mechanisms to enable resource-limited smart objects to verify a claimed access right without relying on central authorization systems. In this paper, we present a novel smart contract-based cross-domain authentication and access control mechanism for applicationcentric IoT. Specially, we propose a proof-of-edge computing node consensus protocol to avoid centralization in practice. The security analysis and experimental results demonstrate that MicrothingsChain is suitable for practice.