IET Blockchain最新文献

Most blockchain users run light nodes on mobile devices. Due to limited storage and computation, light nodes cannot perform transaction validation. This shortage makes opportunities for malicious nodes to produce blocks containing invalid transactions, which results in the loss of funds for light nodes. Fraud proofs play a significant role in ensuring transaction security for light nodes. However, existing fraud proof schemes require honest collaborators and the processing of entire blocks. To address these limitations, Independent Single Transaction Verification Protocol for Light node Using Fraud Proofs without Collaborator called ISTVP is proposed that enables light nodes to independently verify transactions and generate fraud proofs without relying on collaborators or processing the entire block. To support ISTVP, SVST is introduced, an efficient block structure for single-transaction verification. SVST not only efficiently indexes historical transaction outputs to improve verification efficiency, but also significantly reduces the storage requirements for verifying transactions to $��O�\left(��h�+�\log �n��\right)�$. Furthermore, the authors analyze the security of ISTVP and demonstrate that it satisfies both persistence and liveness, while maintaining the level of security of full node.

Payment channel networks (PCNs) are one of the most promising off-chain solutions to the blockchain scalability problem. However, most current payment channel schemes suffer from overly ideal routing assumptions or fail to provide complete path privacy protection. To address the above problems, the multi-hop anonymous and privacy-preserving PCN scheme are analyzed and a multi-hop anonymous PCN based on onion routing is proposed based on it. The scheme removes the routing assumptions of the original scheme, designs an onion routing-based payment channel network, and modifies the way relay nodes construct elliptic curve discrete logarithmic problems to resist wormhole attacks. Finally, the security analysis shows that the scheme in this paper has atomicity, relational anonymity and resistance to wormhole attacks. The latest bilinear pairing anonymous multi-hop payment (EAMHL+) scheme is used to compare communication and computing overhead. The results show that the scheme in this paper requires less communication overhead and is more efficient in terms of computational overhead when the average hop number of the payment channel network is 3 hops and the network diameter is 6 hops.

Blockchain technology has become an emerging area in recent years due to its capacity to improve the security, dependability, and resilience of distributed systems. Research based on this technique has impacted several firms, including banking, healthcare, data processing, remote sensing, and many others. The key characteristics of blockchain technology that make it appealing are data immutability, transparency, privacy, decentralization, and distributed ledgers. However, there is a chance of a privacy breach with sensitive biometric data. The purpose of this investigation is to examine blockchain-based biometric applications research. It begins by determining the myriad ways that biometrics and blockchain may work together, including the storage and protection of biometric templates, identity management, and biometric authentication systems. Different biometric applications with respect to blockchain technology are also identified, along with the types of biometric data taken into account, features and capabilities of blockchain technology exploited, and blockchain technology frameworks employed. Finally, the authors seek to investigate blockchain concepts in the biometric domain by evaluating their pros and cons and summarizing the methods developed on blockchain for diverse biometric applications. Additionally, the applications of blockchain-based biometric systems are highlighted before moving on to open research questions and potential future research areas.

There are service communities with different functions in the Bitcoin transactions system. Identifying community categories helps to further understand the Bitcoin transactions system and facilitates targeted regulation of anonymized Bitcoin transactions. To this end, a Bitcoin service community classification method based on Random Forest and improved K-Nearest Neighbor (KNN) algorithm is proposed. First, the transaction characteristics of different types of communities are analyzed and summarized, and the corresponding transaction features are extracted from the address and entity levels; then multiple classification algorithms are compared, the optimal model to filter the effective features is selected, and the feature vector of entity addresses is constructed. Finally, a classification model is constructed based on Random Forest and improved KNN algorithm to classify the entities. By constructing different classification models for experimental comparison, the accuracy and stability advantages of the proposed method for classification in service community classification research are verified.

Folding at Home community gathers pecuniary crypto interest to an altruist cause (medical drugs research participation). There are many possibilities of ‘teams’ for folding, some of which allow compensation in cryptomonies. The authors will therefore study the three major communities in order to compare them, in a cost-benefit study logic. A cost-benefit analysis was performed between CURECOIN, BANANO, DOGECOIN folding, DOGECOIN mining and their communities on social platforms based on several outcomes: ‘Points Per Day (PPD)’, ‘Whattomine Mh/s Equivalent’, ‘Graphics Processing Units (GPU) Thermal Design Power/Typical Board Power Watts’, ‘Coins per 1,000,000 PPD’, ‘Coins per Day’, ‘Cost Per Coin’, ‘Cost Per Day’, ‘kWh Used Per Day’. Actually, BANANO, thanks to a large community and bots, has the highest PPD production and the lowest energetic cost on Central Processing Unit per week. On GPUs, DOGECOIN folding has the lowest weekly cost. However, the DOGECOIN community cannot produce as many PPD as the Banano team. CURECOIN offers a good compromise between the environmental point of view and the profitability one. To ensure fairness, the choice of the crypto and the way to earn it that has to be solved should be a pure public good, that is, perfectly non-rival in consumption and non-excludable. Indeed, the primary goal of those three communities is to allow scientific progress (thanks to Folding at Home) before allowing a return on investment.

Blockchain smart contracts are codes that can execute and enforce rules for blockchain digital transactions. However, smart contracts may contain numerous subtle vulnerabilities, among which Ponzi vulnerabilities are notable. Existing Ponzi scheme contract detection approaches often rely on machine learning models trained on manually extracted features to achieve satisfactory classification results. Nonetheless, the code of a smart contract potentially harbours elusive semantics and characteristics, which compromises the precision and accuracy of vulnerability detection. Therefore, this paper proposes a method of converting operation codes into sequences to process data to avoid losing unnecessary important information, and uses a one-dimensional convolutional neural network combined with formal verification. This method is named PZ-C1DZ3(Ponzi-Conv1D-Z3) and is used for Ponzi scheme detection. Four types of machine learning models, namely Conv1D, Conv1D-LSTM, Conv1D-MLP, and Conv1D-transformer, are employed for improvement and comparative validation experiments. Additionally, formal verification tool Z3 solver is utilized to conduct formal security verification on the final model, ensuring its safety. Experimental results demonstrate that the improved Conv1D model outperforms other existing models in terms of detection efficiency and accuracy while also meeting the requirements of formal security verification.

The modern world has its foundation built on data. Data is generated all the time, and many aspects of the society and economy are built upon it. In today's world, data is employed in better decision-making, innovation, and improving the efficiency of systems. It becomes essential to protect it from being tampered with or misused. Encryptions based on cryptographic systems are used in mainstream data protection these days. There have been newer iterations of mechanisms based on new techniques using blockchain and the zero trust model and even systems that employ fog computing along with content delivery networks. The advent of computation through quantum technologies also helped in developing data security with post-quantum mechanisms. The critical conditions for the working of these mechanisms hinder their adoption primarily. This also leads current systems to lack one or more of these technologies. Thus, the importance of a unified system that can employ quantum technologies effectively becomes prominent and requires a definitive investigation. In this article, a Quantum-IoT-based data protection scheme that can be of value to Industry 4.0 is analyzed. Light is also shed on innovations in quantum computing that can help solve not just current problems but also the future.