Blockchain Environment Research Articles

Access control scheme based on blockchain and attribute-based searchable encryption in cloud environment

With the rapid development of cloud computing technology, how to achieve secure access to cloud data has become a current research hotspot. Attribute-based encryption technology provides the feasibility to achieve the above goal. However, most of the existing solutions have high computational and trust costs. Furthermore, the fairness of access authorization and the security of data search can be difficult to guarantee. To address these issues, we propose a novel access control scheme based on blockchain and attribute-based searchable encryption in cloud environment. The proposed scheme achieves fine-grained access control with low computation consumption by implementing proxy encryption and decryption, while supporting policy hiding and attribute revocation. The encrypted file is stored in the IPFS and the metadata ciphertext is stored on the blockchain, which ensures data integrity and confidentiality. Simultaneously, the scheme enables the secure search of ciphertext keyword in an open and transparent blockchain environment. Additionally, an audit contract is designed to constrain user access behavior to dynamically manage access authorization. Security analysis proves that our scheme is resistant to chosen-plaintext attacks and keyword-guessing attacks. Theoretical analysis and experimental results show that our scheme has high computational and storage efficiency, which is more advantageous than other schemes.

Blockchain-driven operation strategy of financial supply chain under uncertain environment

The emergence of blockchain creates a new possibility to solve the fraudulent problem of financial supply chain. We construct a game model to verify the strategic choice of the financial supply chain in an uncertain environment. We derive the equilibrium results and investigate the strategic choice of blockchain service for the financial supply chain. We also study the product price, product quantity, financing interest rate, and supply chain risk transmission, respectively. Specifically, when the blockchain is not considered, the financial model of supply chain led by core enterprises depends on firms’ reputation. The retail and wholesale prices increase when fraud occurs or consideration payment increases. Besides, the market stability reduces price performance. In the blockchain environment, the strategic choices are divided into two cases: when choosing the core enterprise model and the third-party service model, the third-party service model is the equilibrium strategy; when choosing the third-party service model and the platform model, the platform model is the equilibrium strategy.

SIAEF/PoE: Accountability of Earnestness for encoding subjective information in Blockchain

Blockchain technology has the potential to be applied widely in supply chain operations. One such area is proactive supply chain risk management (SCRM). In this area, existing researchers have highlighted the fraudulent behaviour of supply chain partners who do not disclose information on the risks that impact their operations. Blockchain can address this problem by encoding each partner’s commitment to SCRM and achieve consensus. However, before this can be achieved, a key challenge to address is the inability of existing consensus mechanisms such as Proof of Work (PoW), Proof of Authority (PoA) and Proof of Stake (PoS) to deal with information that does not have a digital footprint. In this paper, we address this gap by proposing the Proof by Earnestness (PoE) consensus mechanism which accounts for the authenticity, legitimacy and trustworthiness of information that does not have a digital footprint. We also propose the Subjective Information Authenticity Earnestness Framework (SIAEF) as the overarching framework that assists PoE in achieving its aim. We test the applicability of SIAEF and PoE in a real-world blockchain environment by deploying it as a decentralized application (Dapp) and applying it in BscScan Testnet which is an official test blockchain network.

FRAUDULENT PRACTICES AND BLOCKCHAIN ACCOUNTING SYSTEMS Authors Umesh S. Mahtani

Double-entry accounting has been used globally for the past six hundred years and has become the base for all corporate financial reporting. Blockchain technology with distributed ledger now provides a new method of accounting termed “triple-entry accounting”. This method consists of recording and storage of business transactions, as a third entry on the blockchain. This third entry is expected to deliver a system that is trustworthy, immutable, and transparent. This study conducts a detailed review of the present literature on triple-entry accounting with blockchain technology and its impact on fraudulent practices. The review shows current literature has limited information on how this methodology will deter financial and accounting fraud. Drawing on the case studies of twenty-four companies involved in fraudulent practices globally, this paper describes common practices in manipulating financial statements, falsifying accounting records, and fraudulent banking transactions. The study explains the mechanics of how these practices can be prevented using triple-entry accounting in the blockchain environment and how the technique will bring about changes in the audit process and in the roles of internal and external auditors in the organization. The study recommends research propositions focused on governance and financial performance of a company when this method is adopted.

DDS: Deepfake Detection System through Collective Intelligence and Deep-Learning Model in Blockchain Environment

With the spread of mobile devices and the improvement of the mobile service environment, the use of various Internet content providers (ICPs), including content services such as YouTube and video hosting services, has increased significantly. Video content shared in ICP is used for information delivery and issue checking based on accessibility. However, if the content registered and shared in ICP is manipulated through deepfakes and maliciously distributed to cause political attacks or social problems, it can cause a very large negative effect. This study aims to propose a deepfake detection system that detects manipulated video content distributed in video hosting services while ensuring the transparency and objectivity of the detection subject. The detection method of the proposed system is configured through a blockchain and is not dependent on a single ICP, establishing a cooperative system among multiple ICPs and achieving consensus for the common purpose of deepfake detection. In the proposed system, the deep-learning model for detecting deepfakes is independently driven by each ICP, and the results are ensembled through integrated voting. Furthermore, this study proposes a method to supplement the objectivity of integrated voting and the neutrality of the deep-learning model by ensembling collective intelligence-based voting through the participation of ICP users in the integrated voting process and ensuring high accuracy at the same time. Through the proposed system, the accuracy of the deep-learning model is supplemented by utilizing collective intelligence in the blockchain environment, and the creation of a consortium contract environment for common goals between companies with conflicting interests is illuminated.

Secure Data Transactions based on Hash Coded Starvation Blockchain Security using Padded Ring Signature-ECC for Network of Things

Blockchain is one of the decentralized processes in a worldview that works with parallel and distributed ledger technology, the application process, and service-oriented design. To propose a Secure data Transaction based on Hash coded Starvation Blockchain security using Padded Ring signature-ECC for Network of Things. Initially, the crypto policy is authenticated based on the user-owner shared resource policy and access rights. This creates a Public blockchain environment with a P2P Blockchain network. The owner encrypts the data using optimized ECC through Hash-coded Starvation Blockchain security (HCSBS). This makes the encrypted block's provable partition chain Link (P2CL). The encrypted blocks are transmitted into the network of nodes monitored by NoT. During the data transmission, the Network of Things monitors the transaction flow to verify the authenticity over the network of nodes. The monitored data be securely stored in transaction Block storage with the hash-indexed block with chain ring policy (HICLP). This creates controller node aggregation over the transaction environment to securely transfer the data to the peer end. The User gets the access Key to decrypt the data with policy aggregated shared resource policy to access the data. The proposed system produces high security as well compared to the previous design.

An Intelligent Optimization Control Method for Enterprise Cost Under Blockchain Environment

This paper uses blockchain technology to conduct in-depth research and analysis on enterprise cost optimization control. Based on the analysis of the cost control status in enterprises, the concept of target cost optimization control and specific control ideas are proposed. And the study of optimization control under target cost based on genetic algorithm is carried out in combination with the current three major controls of quality, schedule, and cost. It provides the technical basis for the realization of the target profit of the enterprise. The Optimized Scalable Byzantine Fault Tolerance (OSBFT) algorithm, which is suitable for spectrum sharing, is proposed based on PBFT (Practical Byzantine Fault Tolerance) algorithm. So, in this paper, an improved consensus algorithm OSBFT (Optimized Scalable Byzantine Fault Tolerance) is proposed based on it. The improved genetic algorithm is used to solve the objective function and verify the validity, reasonableness and applicability of the model and algorithm. It is shown that the introduction of delay cost in the multilevel inventory model reduces the total cost of the optimized model by 16.87% compared to previous studies. The algorithm reduces the consensus steps, incorporates a data synchronization mechanism, and enables nodes to join and exit consensus.

Kripto kao predmet ugovorne obligacije prema Uredbi o tržištima kripto imovine (MICA) i Zakonu o digitalnoj imovini

The paper examines the legal status and treatment of crypto assets in the context of contractual obligations. The analysis begins by considering the evolution from cryptocurrencies to crypto-goods, with special reference to definitions and terms used in the context of private law transactions. Then, the author focuses on the contractual parties under the EU Regulation on Markets in Crypto Asset (MiCa, 2023) and the Serbian Digital Assets Act (DA Act, 2020), where crypto-assets are predominantly treated as investment assets. Special attention is given to e-money tokens in the context of monetary obligations, as well as to Non-fungible tokens (NFTs) that have not yet been covered by regulations. The paper also refers to the contracting of crypto services, exploring how contractual relationships are formed and regulated, and elaborating on legal transactions based on contracts within the blockchain environment and tokenization. In conclusion, the paper draws attention to the problematic terminology used in the Serbian Digital Assets Act (2020), stating that the term "digital asset" (srb. "digitalna imovina") is too broad and inadequate, and proposes the term "crypto asset" (srb. "kripto dobro") which is defined through two key elements: the private nature of the good and the use of cryptography within the Digital Ledger Technology (DLT). This paper correlates the general theory of contract law and nominate contracts when the contractor's performance is in crypto.

Adaptive Storage Optimization Scheme for Blockchain-IIoT Applications Using Deep Reinforcement Learning

Blockchain-IIoT integration into industrial processes promises greater security, transparency, and traceability. However, this advancement faces significant storage and scalability issues with existing blockchain technologies. Each peer in the blockchain network maintains a full copy of the ledger which is updated through consensus. This full replication approach places a burden on the storage space of the peers and would quickly outstrip the storage capacity of resource-constrained IIoT devices. Various solutions utilizing compression, summarization or different storage schemes have been proposed in literature. The use of cloud resources for blockchain storage has been extensively studied in recent years. Nonetheless, block selection remains a substantial challenge associated with cloud resources and blockchain integration. This paper proposes a deep reinforcement learning (DRL) approach as an alternative to solving the block selection problem, which involves identifying the blocks to be transferred to the cloud. We propose a DRL approach to solve our problem by converting the multi-objective optimization of block selection into a Markov decision process (MDP). We design a simulated blockchain environment for training and testing our proposed DRL approach. We utilize two DRL algorithms, Advantage Actor-Critic (A2C), and Proximal Policy Optimization (PPO) to solve the block selection problem and analyze their performance gains. PPO and A2C achieve 47.8% and 42.9% storage reduction on the blockchain peer compared to the full replication approach of conventional blockchain systems. The slowest DRL algorithm, A2C, achieves a run-time 7.2 times shorter than the benchmark evolutionary algorithms used in earlier works, which validates the gains introduced by the DRL algorithms. The simulation results further show that our DRL algorithms provide an adaptive and dynamic solution to the time-sensitive blockchain-IIoT environment.

ZkChain: A privacy‐preserving model based on zk‐SNARKs and hash chain for efficient transfer of assets

AbstractAs a distributed public ledger technology in a peer‐to‐peer network, blockchain has been widely used in a variety of Internet interaction systems in recent years, such as market supervision, property rights protection, and digital identity. However, in blockchain environment, all historical transaction data are open and transparent, and adversaries may illegally access private transaction data, which makes privacy attacks a core issue that hinders the popularization and application of blockchain. Different privacy‐preserving technologies such as zerocoin and zerocash have been proposed. However, the large amount of proofs and the slow verification speed hinder the effective application of zero‐knowledge proofs (ZKPs) in blockchain. This article proposes a privacy‐preserving model based on zk‐SNARKs and hash chain for efficient transfer of assets, called zkChain. Different from traditional privacy‐preserving schemes, this scheme constructs a smaller proof based on hash chain, and the verification speed of the proof is faster. This scheme constructs ZKP based on the one‐way hash function and zk‐SNARKs. The proof is publicly recorded in the ledger after being verified by miners, and users use the proof to send privacy‐preserving transactions. In the above process, the zkChain scheme can achieve effective privacy protection of account balance and account address. We evaluated the computational and storage costs of the zkChain scheme based on libsnark, and establish a test network to evaluate the processing performance of the zkChain scheme.

Distributed operation optimization of active distribution network with P2P electricity trading in blockchain environment

With the increasing integration of distributed generators and the rapid development of electricity markets, active distribution networks (ADNs) confront new challenges in operation optimization. Centralized optimization methods usually aggravate the computational burden when applied to large-scale distribution networks (DNs). A distributed operation optimization model incorporating peer-to-peer (P2P) electricity trading in a blockchain environment is proposed in this paper, where network usage fees considering electrical distance are specially addressed. Meanwhile, the private information security of prosumers is ensured by the Proof-of-Authority (PoA) consensus blockchain during P2P electricity trading. The trading information of adjustable prosumers should be sent to the proxy entity authorized by the DN using the blockchain platform. In addition, a network partitioning method via dynamic reconfiguration considering multi-level switching is offered to adapt to the required distributed manner. The operation network, as well as the corresponding market structure can be automatically updated according to the results of dynamic reconfiguration. Moreover, the unit price of network usage fees can be adjusted to derive a higher amount of P2P electricity trading with security constraints. Case studies on a practical 148-bus system and a 297-bus system verify that the proposed model maximizes the profits and reduces the computational time in the distributed operation optimization.

Risk prediction and credibility detection of network public opinion using blockchain technology

This study aims to improve the accuracy of risk prediction and credibility detection of network public opinion (NPO) and optimize the network environment. Using blockchain technology (BT) network system for optimization, a smart contract is used to build a risk management system of NPO, so that public opinion can be traced through the smart ledger using risk association tree technology. First, BT, NPO, and related theories of risk management are introduced. Second, the network situation of public opinion dissemination in the blockchain environment is discussed. Finally, a BT-based risk management model of the NPO is implemented, and experiments are conducted to verify the effect of the model. Furthermore, the theoretical framework of NPO credibility model detection is optimized according to the public opinion risk prediction model. The research results reveal that the three experimental schemes reached the peak density of the number of public opinion disseminators in the third step, and the highest values were 0.1335, 0.1318, and 0.1296, respectively. Moreover, the density of public opinion dissemination in the three experimental schemes reached a stable state of 0.087, 0.088, and 0.0898, respectively after 48 steps. Under BT, the designed three experimental schemes can reasonably conduct the risk prediction and credibility detection of NPO. This work contributes to optimizing the control measures of the network environment.

Decentralized peer-to-peer energy trading strategy in energy blockchain environment: A game-theoretic approach

With the proposed concept of energy blockchain, peer-to-peer (P2P) energy trading between prosumers is regarded as a potential way for future power market development. However, existing P2P energy trading often has problems such as low trading efficiency and significant communication losses. This paper presents an energy trading strategy in the blockchain environment to solve the problems of P2P energy trading. First, the type of market is determined based on energy supply and demand. Then, a Stackelberg game is used to establish a two-layer model of the leader (upper) and follower (lower) to determine the price. In addition, we propose an energy trading method based on feasible regions. The trading strategy considers the supply and demand of the market, provides an accurate energy transfer signal, and can help energy blockchain achieve better “self-sufficiency”. A case study proves the effectiveness of the strategy. Compared with the existing methods, the strategy proposed in this paper considers the market type and can promote the coordination and complementation of energy in the microgrid, and improve trading efficiency and reduce communication loss without sacrificing privacy. This study demonstrates that P2P power trading has brought benefits to prosumers, has promoted the development of the energy market, and has shown the massive potential of energy blockchain.

Ethereum Application for Product Anti-Counterfeiting

The project's goal is to create an application that assures consumers don't have to rely solely on merchants to determine whether or not products are authentic. It also assures that producer may use this system to supply genuine products without having to run direct operated outlets, lowering product quality assurance costs dramatically. The trade in counterfeit goods is expanding, hurting the sales and earnings of businesses who are affected. This project proposes a fully-functional blockchain system to prevent product counterfeiting to ensure the identification and traceability of real products throughout the supply chain. Establishments only need to pay minimal transaction fees, and they no longer need to be concerned about the probability of obtaining counterfeit products. This project utilizes Ethereum blockchain and Remix to develop the application code in the form of a Smart Contract. For testing and implementation, Ganache and MetaMask are used, which simulates the blockchain environment and user account respectively. The Client-Side application leverages with Reactjs and Web3js to interact with smart contract and provide its functionalities to the users, maintaining the integrity of the system. Key Words: Ethereum, Anti-Counterfeit, Solidity, Web3js, Reactjs, Ganache

Efficient and privacy-preserving decentralized energy trading scheme in a blockchain environment

Blockchain technology provides the possibility for the realization of decentralized energy trading. However, the blockchain confronts privacy risks and efficiency issues, which hinder its application in energy trading. In this paper, to solve this problem, we propose an efficient and privacy-preserving decentralized energy trading scheme in a blockchain environment. We propose an account mapping algorithm to solve the privacy attack problem. We propose a new transaction processing method, which can protect private data and improve execution efficiency by two-layer transaction processing. Finally, we verify the effectiveness of the proposed scheme for privacy protection and trading efficiency of decentralized energy transactions through experiments.

A Blockchain-Based Secure Multi-Party Computation Scheme with Multi-Key Fully Homomorphic Proxy Re-Encryption

At present, secure multi-party computing is an effective solution for organizations and institutions that want to derive greater value and benefit from the collaborative computing of their data. Most current secure multi-party computing solutions use encryption schemes that are not resistant to quantum attacks, which is a security risk in today’s quickly growing quantum computing, and, when obtaining results, the result querier needs to collect the private keys of multiple data owners to jointly decrypt them, or there needs to be an interaction between the data owner and the querier during the decryption process. Based on the NTRU cryptosystem, which is resistant to quantum computing attacks and has a simple and easy-to-implement structure, and combined with multi-key fully homomorphic encryption (MKFHE) and proxy re-encryption, this paper proposes a secure multi-party computing scheme based on NTRU-type multi-key fully homomorphic proxy re-encryption in the blockchain environment, using the blockchain as trusted storage and a trusted execution environment to provide data security for multi-party computing. The scheme meets the requirements of being verifiable, conspiracy-proof, individually decryptable by the querier, and resistant to quantum attacks.

An Intelligent Secure Monitoring Phase in Blockchain Framework for Large Transaction

Blockchain is the key concept for security purposes for digital applications. But, in some cases, the effectiveness of the malicious behavior has degraded the security function of the blockchain. So, to enrich the blockchain process prediction and to neglect the malicious event from the data broadcasting medium is very important. So, the current research article intends to develop an efficient monitoring strategy based on incorporating deep features. Hence, the designed paradigm is termed as Lion-based Convolutional Neural Model (LbCNM) with serpent encryption. Before performing the encryption process, the novel LbCNM parameters have been activated to monitor the data process channel in the blockchain environment. Here, the malicious behaviors were estimated by incorporating the known and unknown user behavior in the Lion fitness model. During the execution, the fitness formulation of Lion is acted in the classification layer of the convolutional model. Once the present malicious characteristics have been detected, it is neglected from the data broadcasting channel. Hereafter, the transactional data has been encrypted and stored in the specific cloud. The planned strategy is verified in the python platform. The successful performance of the LbCNM with serpent has been analyzed with some key parameters like confidential rate, accuracy, data overhead, and processing time.

Behavior analysis of photovoltaic-storage-use value chain game evolution in blockchain environment

In view of the stability of photovoltaic utilization and trust in transactions, this paper constructed a photovoltaic-storage-use value chain in the block chain environment, and studied the behavioral strategies of photovoltaic power generators, energy storage providers and users in the value chain by using a three-party evolutionary game model. This paper analyzes the influence of the initial willingness of game players, the cost and utilization degree of blockchain technology, government subsidies, the price reduction coefficient of users, and the loss of photovoltaic-storage being wholesaled on the results of evolutionary equilibrium. The results show the cooperation between photovoltaic power generators and energy storage providers will become one of the trends of photovoltaic development in the future, and users will greatly enhance the utilization degree of photovoltaic and realize the value co-creation of the three parties. The decrease of blockchain technology cost, the increase of blockchain utilization, the increase of government subsidies, the increase of user price reduction coefficient, the decrease of photovoltaic-storage loss coefficient of being wholesaled and so on encourage the increase of cooperation of photovoltaic power generators and energy storage providers, and users' behavior of using photovoltaic. These results can provide some reference for the development of photovoltaic and energy storage industry.

Towards Fair and Decentralized Federated Learning System for Gradient Boosting Decision Trees

At present, gradient boosting decision trees (GBDTs) has become a popular machine learning algorithm and has shined in many data mining competitions and real-world applications for its salient results on classification, ranking, prediction, etc. Federated learning which aims to mitigate privacy risks and costs, enables many entities to keep data locally and train a model collaboratively under an orchestration service. However, most of the existing systems often fail to make an excellent trade-off between accuracy and communication. In addition, they overlook an important aspect: fairness such as performance gains from different parties’ datasets. In this paper, we propose a novel federated GBDT scheme based on the blockchain which can achieve constant communication overhead and good model performance and quantify the contribution of each party. Specifically, we replace the tree-based communication scheme with the pure gradient-based scheme and compress the intermediate gradient information to a limit to achieve good model performance and constant communication overhead in skewed datasets. On the other hand, we introduce a novel contribution allocation scheme named split Shapley value, which can quantify the contribution of each party with a limited gradient update and provide a basis for monetary reward. Finally, we combine the quantification mechanism with blockchain organically and implement a closed-loop federated GBDT system FGBDT-Chain in a permissioned blockchain environment and conduct a comprehensive experiment on public datasets. The experimental results show that FGBDT-Chain achieves a good trade-off between accuracy, communication overhead, fairness, and security under large-scale skewed datasets.

Cloud Storage Model Based on the BGV Fully Homomorphic Encryption in the Blockchain Environment

Blockchain is a distributed time-series database. Based on the blockchain platform, this paper designs the framework model of cloud storage and designs the cloud storage model based on homomorphic encryption based on the operation process of the model. According to the applicability of underlying blockchain storage, the HElib library is established as the algorithm for data privacy protection. The BGV homomorphic encryption algorithm is used as the bottom layer of the algorithm, and the efficiency of the BGV homomorphic encryption algorithm is compared with that of the Gentry’s bootstrap-based homomorphic encryption algorithm. It is proved that the BGV algorithm is more suitable for big data.