6G streaming advancement intensifies challenges in content security, copyright traceability, and privacy protection. This paper proposes a novel architecture integrating federated learning and blockchain. By enhancing protocol stacks and reconstructing trust mechanisms, it delivers an end-to-end solution spanning content creation, auditing, distribution, and value allocation. Federated learning metadata and blockchain interfaces are embedded within RTP/RTCP protocols, establishing a terminal-edge-cloud three-tier auditing system for hierarchical content filtering and localized privacy processing. A smart contract framework enables digital rights confirmation and value circulation through decentralized incentives and token-driven economics. Performance analysis confirms significant improvements in auditing efficiency and copyright transparency while maintaining ultra-low latency and supporting multimodal experiences, providing a systematic paradigm for secure, trustworthy streaming ecosystems.
Trading is an effective way to exchange resources such as energy, data, and computing services between Internet of Things (IoT) for mutual benefit. The emerging blockchain-enabled market facilitates the transparency and traceability of trading, but poses new challenges to the financial stability of the market. The existing blockchain-enabled market framework is designed as a completely free market, and due to the inherent characteristics of blockchain, it is difficult to take effective measures to maintain financial stability. To address this challenge, we propose a regulated blockchain-enabled market framework for IoT devices. Based on the heterogeneous interacting agent theory in economics, we study the price dynamics and equilibrium in the market. We establish a trading smart contract that supports trading among IoT devices, and provides the market regulator with interfaces to adjust the regulatable factors in the market to promote financial stability. A prototype system of our framework is implemented in Ethereum. The experimental results demonstrate the low execution cost of the smart contract, the correctness of our theoretical analysis for the market, and the effectiveness of the regulatory policies.
With the increasing popularity of high-frequency trading and decentralized finance (DeFi) applications, it has become essential to implement protections for regular users of DeFi platforms against large parties with massive amounts of resources, allowing them to engage in market manipulation strategies like the maximum extractable value (MEV). MEV can be extracted using the Bellman-Ford flow algorithm, making it easy for bots to realize MEV in DeFi. In classical trading, front-running is illegal and is classified under the umbrella of insider trading. However, the classical approaches to the mitigation of MEV do not apply to DeFi applications, as the mitigation of classic insider trading is based on central enforcement through legal laws. DeFi has in it both blockchain platforms and automated market makers (AMM) on decentralized exchanges (DEX), which introduces additional stakeholders that are virtual/anonymous for which the fear of legal laws/suits do not apply. Hence, a variety of approaches have been proposed in the literature to overcome or minimize MEV. In this paper, first, we illustrate various MEV attacks in classical trading, show how MEV can be exploited algorithmically, and discuss mitigation techniques to overcome MEV in classical trading. Secondly, we show that the same mitigation techniques for overcoming MEV in DeFi do not apply as additional stakeholders are introduced. Thirdly, we describe the design of a robust AMM on XRPL blockchain ledger that overcomes MEV. From such a design on XRPL which is one of the widely used blockchain platforms that has several constraints as compared to the general permissionless or permissioned blockchain platforms, we discuss issues of overcoming MEV in general DeFi applications. It is argued that such limitations necessitate a practical regulatory approach supported by a good forensic methodology with tools to instill confidence in the use of DeFi.
This paper explores the application of blockchain technology in managing and sharing medical data, focusing on the use of Non-Fungible Tokens (NFTs) and the InterPlanetary File System (IPFS) to enhance data security, privacy, and interoperability. Traditional methods of data management in healthcare face significant challenges, including data fragmentation, security vulnerabilities, and lack of interoperability among diverse systems. Blockchain technology, with its decentralized and immutable nature, offers a robust solution to these challenges. We provide a comparative analysis of transaction fees across four Ethereum Virtual Machine (EVM)-compatible platforms—BNB Chain, Fantom, Polygon, and Celo—to assess their suitability for medical data management. The study evaluates key operations, such as initiating transactions, minting NFTs, and transferring NFTs, which are essential for the secure and efficient handling of medical records. By examining these platforms, this paper aims to identify a cost-effective blockchain solution that balances operational expenses with performance requirements. The findings contribute to the ongoing development of secure, transparent, and reliable systems for managing medical data in healthcare settings.
In this paper, we design a decentralized drone delivery platform named CoEat. The article describes the necessity of the CoEat platform and the birth of DeFi economy, and elaborates on the three development stages of the platform in detai. Finally, the article will further discuss the innovative technologies applied in platform development and provide prospects for the platform’s future growth.
In supply chain management, a common scenario lies in proving an entity’s ability, e.g., a supplier needs to prove its supplying ability by revealing its commodity transactions often have quantity constraints (e.g., minimum order quantity and maximum supply capacity). However, traditional verification mechanisms require the trading participants to disclose their core business secrets, which poses significant risks of commercial privacy leakage. To meet the verification requirements of business constraints while strictly protecting the sensitive data of all participants, this study proposes a verifiable privacy protection protocol based on non-interactive zero-knowledge range proof and blockchain technology. The core innovation of this framework lies in enabling suppliers to generate and submit cryptographic proofs to purchasers (namely as a verifier) without revealing their exact production capacity, thereby efficiently and reliably proving their ability to meet specific transaction quantity requirements. In addition, the process is designed atop blockchain, which, acting as an infrastructure of supply chain, plays the role of recording immutable transactions of proofs and coordinating participants. Security analysis is performed and experiment is conducted to showcase the protocol’s efficacy and efficiency.
This study proposes a blockchain benchmarking system based on distributed architecture and network simulation techniques, aiming to overcome the performance limitations and network edge effects of traditional single-machine benchmarking schemes. By integrating Docker containerization and the Linux TC tool, the system simulates blockchain network topologies with customizable connection and latency matrices, enabling the rapid construction of diverse network configurations. In addition, leveraging Zookeeper to coordinate multiple testing machines enables a distributed benchmarking process. This breaks through single-machine performance bottlenecks and minimizes interference from network edge conditions. The experimental results demonstrate that the system effectively evaluates the scalability, stability, and performance of the data layer of blockchain systems. For example, under a high-latency network with a 132-ms delay, the TPS of PBFT-based blockchains drops significantly. PoW-based systems show stronger resilience. This system provides a robust and realistic testing platform for blockchain performance evaluation and optimization, supporting practical deployment in real-world scenarios.
As the value of decentralized finance (DeFi) continues to increase, it has become an increasingly sought-after area within blockchain technology. However, the accompanying Maximum-Extractable Value (MEV) issue has begun to raise concerns. MEV is closely related to transaction ordering, which makes sequencers with ordering power the primary target for participants seeking to manipulate transaction ordering for profit. This undermines market fairness and causes losses for other users. To address this issue, this paper introduces MEVShield-an anti-sequencer manipulation framework that uses a secret election mechanism to protect sequencers from malicious threats. MEVShield employs a secret election mechanism to keep sequencer identities confidential, ensuring the security of sequencers and the fairness of transaction sequencing. We conducted a comprehensive security analysis and implemented MEVShield to evaluate its performance. The experimental results demonstrate that the proposed scheme achieves a high level of security while maintaining acceptable computational and communication costs.
The automotive industrial value chain is a highly integrated network that connects multiple stakeholders, allowing seamless coordination from product design to final delivery to users. However, the industry is often constrained by challenges such as data silos and trust deficits, which impede effective collaboration in core business processes, thus affecting operational efficiency and overall profitability. To address these issues, blockchain emerges as a promising solution to facilitate value chain collaboration in the automotive industry. As a decentralized infrastructure and computing paradigm built on a peer-to-peer (P2P) network, blockchain offers a trustworthy mechanism for value transfer. In this paper, we summarize the key functionalities of blockchain and present a conceptual framework for a blockchain-enabled automotive industrial value chain. The feasibility of blockchain adoption is theoretically analyzed through an industry application. In addition, we identify potential challenges and propose countermeasures, providing insight into the practical implementation of blockchain in the automotive industry.
Blockchain serves as the cornerstone of decentralized trust and distributed data management in the Web3 era. Its applications have expanded from decentralized finance (DeFi) to various industrial and societal sectors. As one of the most recognized foundations behind those blockchain systems, the proof-of-work (PoW) consensus mechanism suffers from excessive computational and energy consumption. Encountering this challenge, a number of projects such as Quilibrium, Qubic, and TIG have pioneered several initiatives, including proof-of-stake (PoS) and useful proof-of-work (UPoW), to lower blockchain’s reliance on hard and intensive hash trails. However, these initiatives still encounter challenges related to wasted computation resources, procedural complexity, incentive fairness, and centralization concerns. In this work, we propose a route-planning-based consensus mechanism that transforms the route-planning works into useful mining puzzles of the blockchain consensus procedure. We conduct a comprehensive analysis of the mining puzzle, design a problem-solving algorithm as the fair and efficient consensus mining process. We employ a series of experiments to evaluate the performance of the proposed mining puzzle and the problem-solving algorithm and demonstrate their effectiveness in converting the majority of computational effort into useful work.
Open business model in MEC is conductive to resources sharing of consumer electronic products. However, there are risks in the process of business mode opening, such as, the protection and smart management of data and knowledge flow. Based on the blockchain, smart contract and DAC (Distributed Autonomous Corporation) technologies, we propose the Blockchain-based business model (called BM-ICB) of open innovation strategy for smart edge data flow. Based on the DPoS consensus mechanism of blockchain technology, we research the smart and dynamic management mechanism to realize the detection, monitoring and classification of enterprise behaviors of consumer electronic products, besides, the interaction process between the users and Consortium chain is improved through the DAC technology. The theoretical analysis estimates strong security and high performance of the BM-ICB model, and the experimental evaluation testifies the high performance.
The Lussa Platform introduces a transformative approach to game development by fusing AI, blockchain, and social account abstraction. Amid a backdrop of rising development costs and shrinking funding opportunities, Lussa reimagines the production pipeline through an agentic architecture that deploys intelligent, collaborative agents and blockchain-based token economies. Integrated with the AI Value Protocol (AIVP) and the Horus Wallet, Lussa empowers developers and communities to co-create, govern, and monetize games with dramatically reduced costs and time-to-market. Initial deployment in the game The Final Frontier showed a 50–56
With the growth of decentralized finance (DeFi), non-fungible tokens (NFTs), particularly those based on artistic images, have become mainstream. However, copyright issues are increasingly severe, as forged or plagiarized artworks are minted and resold as NFTs, infringing creators’ intellectual property rights. Despite progress in NFT copyright protection, detection remains post-minting, and the rise of AI-generated models has intensified image forgery and style plagiarism, which existing methods fail to address. We propose ZKP-StylePatch, comprising: (1) a model to detect the origin of artistic images, and (2) a zero-knowledge proof mechanism to verify model output integrity and authenticity. Using GenImage and a style-transferred NFT dataset, experiments show ZKP-StylePatch achieves 91.35
The integration of privacy-preserving computation and blockchain have significantly advanced cross-institutional data sharing in financial regulation. However, challenges of transaction chain reconstruction and private information preservation remain unresolved, which causes illegal activities such as fraudulent trade due to the lack of inter-bank information interoperability. To address these issues, this paper proposes a collaborative supervision that combines Private Information Retrieval (PIR) and blockchain technology. Leveraging the PIR protocol, supervision authority can retrieve transactions associated with suspicious identity from various banks, without disclosing the retrieval target. Furthermore, blockchain is used to record and verify transactions, which helps to automatically correlate multi-account transaction chains and enables verifiable tracing of fund flows. Experimental results demonstrate that the transaction tracing scheme can achieve a single retrieval and batch retrieval with high execution efficiency. The running time only rises to 10.917 s (at 1 × 10^7 data size) for batch retrieval of 1000 data entries, which is within an acceptable range for financial regulatory scenarios
Business process management is a vital technology for managing and analyzing business processes in industrial chain. Blockchain, as a decentralized and tamper-proof distributed ledger technology, emerges as a promising infrastructure to support business process management and collaboration. In industrial chain collaboration, finding the most suitable business department to complete the business task can significantly increase the business execution efficiency. However, one of the critical challenges lies in reliably evaluating a department of its capability of completing the task. Existing related works either rely on subjective selection or the evaluation lacks of verifiability and trustworthiness. To this end, we propose a blockchain-based trusted business department recommendation protocol. Firstly, several dimensions are designed for evaluating local business departments and cross-enterprise collaborated departments. Secondly, a blockchain-based protocol is proposed to accumulatively generate verifiable values of these dimensions. Thirdly, we propose the fuzzy information entropy-enabled weighted fusion of these dimensions and produce comprehensive evaluation results for departments. Finally, the designed smart contracts are implemented and deployed on the Ethereum Sepolia test network, and the experimental results demonstrate efficient on-chain gas cost.
Blockchain applications often rely on lightweight clients to access and verify on-chain data efficiently without the need to run a resource-intensive full node. These light clients must maintain robust security to protect the blockchain’s integrity for users of applications built upon it, achieving this with minimal resources. Moreover, different applications have varying security needs. This work focuses on addressing these two key requirements and identifying the fundamental cost-latency trade-offs to achieve tailored, optimal security for light clients. Staking can provide economic guarantees (like in Proof-of-Stake blockchains). In this paper, we formalize this cryptoeconomic security to light clients, ensuring that the cost of corrupting the data provided to light clients must outweigh the potential profit, then, propose an economically secure light client protocol. We further introduce “insured” cryptoeconomic security to light clients, providing unconditional protection via the attribution of adversarial actions and the consequent slashing of stakes. Moreover, the divisible and fungible nature of stake facilitates programmable security, allowing for customization of the security level according to the specific needs of different applications. We implemented our light client in less than 1000 lines of Solidity and TypeScript code [49] and evaluated their gas cost, latency, and computational overhead. For example, for a transaction valued at 32k, the light client can choose between zero cost with a latency of 5 h, or instant confirmation with an insurance cost of7.45. Thus, the client can select the optimal point on the latency-cost trade-off spectrum that best aligns with its needs. Our light client requires negligible storage and minimal computation, typically verifying only a few signatures (as few as one in most cases).
In an era of evolving property management and ownership practices, blockchain technology emerges as a transformative force and revolutionizes traditional land registration systems. This conceptual approach is a vision of a future world where property transactions occur without glitches. Based on a network of nodes that perform the data distribution, blockchain does not require a central authority (decentralized) and significantly decreases the possibility of data manipulation. Utilizing blockchain's chain of custody and cryptographic features, a land registration system is strongly anticipated to counter existing challenges in the real estate industry, such as fraud, conflicts, and procedural bottlenecks that have been frustrating the industry for decades. The project deploys Solidity-based self-executing smart contracts to automate and enforce agreements related to property transfer, boosting efficiency and cutting out intermediaries. Users self-register and upload the required documents to the system. The critical aspect is that the user is verified only after the inspector meticulously assesses their details using the government database. After assessment, the user can use the application to sell or buy land. The inspector also surveys the land physically before granting permission to make the land available for purchase. The buyer and seller agree on a price before generating the ownership deed. Smart contracts are created for each of these steps from user registration to transfer of ownership, and stored in the local blockchain. Cryptographic algorithm, Hash Algorithm SHA-256 is utilized to protect user's sensitive information and keep anyone from unauthorized access and InterPlanetary File System (IPFS) for file storage.
This paper, based on the well-known problems and the most technical challenges in Blockchain space, studies ground-breaking and critical inventions of various blockchain protocols to give a taxonomy for the evolution of four public Blockchain generations. The first and second generations are well-defined by Bitcoin and Ethereum, respectively. The latest state-of-the-art blockchain protocols have been shaping the third and fourth generations, by their own outstanding innovations and distinguished architectural designs to solve limited capacity and scalability of Bitcoin and Ethereum. This work helps readers quickly capture historical evolution and innovations of public blockchains, envisioning the next advancements of Web3 as well as the Internet of Value (Internet 2.0).
With the exorbitant growth of Internet of Things (IoTs) scale and the interconnections among such a vast realm of heterogeneous objects, it is vital to uniquely identify the IoT devices and build a robust identity management (IdM) system, thus enabling many desired security mechanisms including authentication, authorization and secure exchange. An appealing technology to overcome the shortcomings of conventional online identity models and empower the construction of a robust IoT IdM system lies in decentralized identity, also known as self-sovereign identity. The existing literature on IoT IdM systems omits several critical functionalities like legacy compatibility and consideration of the IoT device lifecycle. In this study, we tackle these issues and present - , a system for realizing secure and robust decentralized identity management in the IoT setting. We elaborate on the system details and give security sketch. Experimental results demonstrate its effectiveness and efficiency.
This paper introduces a novel model for a decentralized perpetual futures AMM protocol, utilizing a family of asymptotic power functions. It enables the construction of permission-less perpetual markets for any underlying asset, provided price feed. We provide a rigorous mathematical formalization, derivative pricing and analysis of the model. It shows that, when properly initialized, a perpetual market is everlasting under any market conditions. Furthermore, the model represents the first-ever power perpetual market to offer no liquidation for traders and no bankruptcy for liquidity providers, breaking away from conventional unique position models and order-book in legacy perpetual exchanges.
