Fair Payment Research Articles

Reflecting on micro‐ethics to center the voices of Aboriginal peoples experiencing homelessness

AbstractThis article shares the micro‐ethical lessons from those researching alongside Aboriginal people experiencing homelessness and Aboriginal Elders in Perth, Western Australia. The article is written from the perspective of the first and second author who are two non‐Aboriginal researchers being mentored in Aboriginal culture. From this positioning, it offers reflections and practical insights into researching “in the right spirit” with Aboriginal communities. More specifically, it shares lessons in negotiating community roles within community‐driven research, the importance in forming relationship with Aboriginal culture as antidote to research fatigue, practical ways to work with Aboriginal communities when they have a history of being exploited in research, navigating fair and ethical payment for involvement, and ways to clearly communicate research with them. It also shares the cultural importance and benefits of working closely with Aboriginal Elders when engaging in research with Aboriginal communities, including their ability to better negotiate project scope with community, and the value in making sense of the research findings alongside them.

Social network, fair payment, subjective well-being, and general health: a moderation mediation analysis.

This research aimed to investigate whether subjective general health mediated the relationship between social networks and subjective well-being and whether the perception of fair payment moderated the mediating effect of subjective general health on subjective well-being. Data were drawn from round 9 of the European Social Survey (ESS), involving 3,843 respondents from 19 countries, with ages ranging from 65 to 90 years (Meanage = 73.88 ± 6.61 years). The participants completed self-reported measures assessing subjective well-being, social networks, subjective general health, and perception of fair payment. Subjective general health played a mediating role in the relationship between social networks and subjective well-being. The perception of fair payment emerged as a moderator in the mediating effect of subjective general health on the association between social networks and subjective well-being. This study suggests that the impact of social networks on both subjective general health and subjective well-being is contingent upon individuals' perceptions of fair payment. These results highlight the significance of social networks in fostering social connections and promoting overall subjective well-being.

A fair multi-attribute data transaction mechanism supporting cross-chain

Reliable storage and high-speed data networks enable individuals to access high-quality Internet of Things (IoT) data for scientific research through global transactions. Blockchain technology provides transparency for institutions to securely store and manage IoT data, while cross-chain transaction mechanisms facilitate the flow of IoT data. However, fairness issues may arise when it comes to cross-chain transactions of IoT data. This paper proposes a mechanism for multi-attribute data transactions to support cross-chain. The solution utilizes Vickrey–Clarke–Groves (VCG) auction, Paillier, Intel SGX, and other technologies to design a secure and equitable data seller selection scheme. The scheme ensures that the selection process for data sellers is both informed and private. Additionally, we generate a key pair for each attribute in the dataset to produce the corresponding attribute data signature. The dataset’s legitimacy is verified through batch verification to ensure that the data seller’s purchased attributes align with their requirements. The exchange of crypto assets and private keys between data sellers and buyers is designed to achieve fair payment. Our research suggests that the scheme meets the necessary security standards, and simulation results confirm its feasibility and effectiveness.

Pengaruh Tunneling Incentive Dan Mekanisme Bonus Terhadap Tax Avoidance: Systematic Literature Review

The importance of taxes in economic development for developing countries, with a focus on tax avoidance as the main obstacle in achieving optimal tax revenues. The aim of this research is to review the influence of bonus mechanisms and tunneling incentives on tax avoidance in companies. This research method uses the Systematic Literature Review (SLR) method to analyze journals and articles published between 2017 and 2024, with a focus on the themes of tax, tunneling incentives, bonus mechanisms and tax avoidance. Of the 59 articles that have been selected, only 57 articles are used as research sources in this journal. The development of the number of publications related to the influence of bonus and tunneling incentive mechanisms on Tax Avoidance is still fluctuating from 2017 - 2024. It can be concluded that bonus mechanisms and tunneling incentives have different roles in influencing tax avoidance. various research sources: incentive tunneling variables can reduce tax avoidance, while bonus mechanism variables can increase tax avoidance. Tax evasion is a complex problem that requires clear consideration and law enforcement by the government and business world to ensure legal and fair tax payment practices.

EFPB: Efficient Fair Payment Based on Blockchain for Outsourcing Services in Cloud Computing

Despite the maturity of cloud services (e.g., outsourcing of computational tasks), a number of operational challenges remain. For example, how do we ensure trust between outsourcers and workers in a zero-trust environment? While a number of blockchain-based solutions that eliminate the reliance on trusted third parties have been presented, many of these existing approaches do not achieve robust fairness and/or support compatibility with other systems. In this paper, we propose an efficient fair payment system using blockchain (EFPB), designed to achieve robust fairness and compatibility. Specifically, EFPB comprises a number of cryptographic building blocks, mainly: one-way accumulator (RSA-based construction), stealth address and symmetric encryption. We then evaluate the performance of EFPB to demonstrate that it is more efficient and low-cost than other competing schemes, as well as presenting a comparative summary of functionalities.

Digital space for payroll and remuneration

The study identifies the features of wage systems that directly affect their implementation in automated programs. The complexity of salary calculation, and sometimes the inability to implement a particular system in an automated program, is the main reason for the rejection of more modern wage systems. A comparative analysis of automated programs has been carried out, which makes it possible for an organization to choose a remuneration system not from the point of view of what the existing automation system offers, but from the point of view of necessity and compliance with the business processes of the organization. This will make it possible to apply more efficient and fair payment systems that will meet current trends and requirements of the labor market. The functional capabilities of the programs in terms of calculation and remuneration are defined. The directions of development and application of digital technologies for calculation and payment of labor are highlighted. The development of new technologies makes it possible to create a digital environment for payment.

SECURED PAYMENT ON BLOCKCHAIN FOR OUTSOURCING SERVICES IN CLOUD COMPUTING

Cloud computing has revolutionized outsourcing services, yet concerns about online payment security and mutual distrust persist. Existing solutions often rely on trusted third parties, limiting their applicability. To address this, we introduce BPay, a novel framework leveraging blockchain technology to enable a payment system that is both secure and equitable.for outsourcing services without intermediaries. We introduce the system framework, adversary model, and objectives of BPay, emphasizing its compatibility with Bitcoin and Ethereum blockchains. Security and compatibility analyses demonstrate BPay's robustness and efficiency. Cloud computing has revolutionized the manner in which outsourcing services are delivered and accessed, offering unprecedented scalability, flexibility, and cost-effectiveness. However, despite its numerous benefits, concerns about the security of online payments and the lack of trust between users and service providers continue to pose significant challenges. Traditional payment systems often rely on trusted third parties to facilitate transactions, which can introduce vulnerabilities and increase the risk of fraud or data breaches. These limitations hinder the broader adoption of cloud computing in various industries and applications. Keywords:efficient fair payment, blockchain-based technology,RSA algorithm,public key private key,security,Encryption-decryption

A Game Model Analysis of the International Digital Service Tax in an Asymmetric Market Duopoly

Against the backdrop of the rapidly expanding digital economy, multinational corporations are increasingly exploiting information asymmetry in the market to employ covert and diverse methods of tax avoidance. This poses a significant challenge to tax collection and administration. The proposal of a digital service tax aims to adapt the international tax system to the digitalization of the economy, ensuring fair and reasonable tax payments. To address these challenges, this article assumes an asymmetric international digital economy market and a domestic market characterized by duopoly. It establishes an asymmetric market duopoly game, calculates the digital gains of each country's market using the logistic function, determines the Nash equilibrium of the data service tax game, and analyzes the relationship between the digital service tax rates of strong and weak countries in the digital economy.

A Bitcoin-based Secure Outsourcing Scheme for Optimization Problem in Multimedia Internet of Things

With the development of the Internet of Things (IoT) and cloud computing, various multimedia data such as audio, video, and images have experienced explosive growth, ushering in the era of big data. Large-scale computing tasks in the Multimedia Internet of Things (M-IoT), such as mathematical optimization problems, have begun to be outsourced from IoT devices with limited computing power to cloud servers for execution. However, outsourcing computation brings security concerns, because the behaviors of clouds are invisible to users. The leakage of privacy data in outsourced optimization problems leads to immeasurable losses. The mutual distrust between clouds and users causes that the correctness of the optimal decisions and the fairness of the payment activities are not guaranteed. Blockchain technology has the characteristic of immutability and has become a new security paradigm for eliminating multi-party trust concerns. In this article, we propose a Bitcoin-based secure outsourcing scheme to address the aforementioned security concerns. To prevent confidential data leakage, the proposed scheme designs a computable privacy-preserving method for the outsourced optimization problems. To judge the correctness of the optimal decision and reduce verification costs, the proposed scheme designs a low-cost two-layer verification mechanism based on dual theory and blockchain technology. Blockchain nodes reach a consensus on the problem solutions and trigger an automatic fair payment protocol-based Bitcoin. Security analysis and experimental results demonstrate that our scheme guarantees privacy, fairness, and computational efficiency.

On the fair scheduling of truck drivers in delivery companies: balancing fairness and profit

AbstractFairness is crucial in transportation systems to ensure that all drivers are treated equally and have the same opportunities. Fair payment policies, equal access to work opportunities, and fair scheduling are some of the policies delivery companies implement to ensure fairness between drivers. In this paper, we study a fair scheduling mixed-integer programming problem where we consider a bi-objective function that aims to maximize profit and improve fairness between drivers by minimizing the maximum deviation from the average driving time. To solve this problem, we employ the weighted comprehensive criterion method and propose an iterative population-based heuristic. The results show that the relative gap between the heuristic and exact approach is acceptable. We also report the fairness price which is the relative difference between total profit with and without incorporating fairness. We find out that improving fairness between drivers does not always lead to a significant reduction in total profit. When the reduction in total profit is important, we recommend formulating the scheduling problem differently where instead of minimizing the maximum deviation from the average driving time, drivers are rewarded when their driving times are longer than the average. We explore incorporating the cost of rewarding these drivers in the objective function.

Managed competition in Aotearoa New Zealand: past experiences and future prospects.

This paper considers whether and how managed competition arrangements could be introduced into the Aotearoa health and disability system. The paper describes the key features of the system, including new organisational arrangements established from 1 July 2022. It discusses major reforms and managed competition plans that were developed in the 1990s, with the managed competition plans abandoned fairly early on, as a result of major issues with the reforms that had been implemented and with problems in designing a fair payment system for competing health plans. The paper goes on to argue that the development of capitated, risk-bearing and competing Primary Health Organisations set up in the 2000s should be considered in terms of managed competition, and the paper points to the issues that have arisen in Aotearoa due to a lack of regulations that would have better supported the better achievement of effectiveness, efficiency, and equity goals over the past 20 years. Finally, the paper also looks ahead to whether and how managed competition might again be considered in Aotearoa and the extent to which the system currently includes key pre-conditions to support such arrangements.

A General Blockchain-Based Automatic Audit Scheme For Proofs Of Retrievability

Abstract Cloud storage has been widely used in remote data management, although correct storage of the outsourced file is still challenging in practice. Proofs of Retrievability (PoRs), a storage-oriented cryptographic tool, support integrity checking and efficient retrieval of the file. However, due to the lack of a fully credible oversight mechanism or a serious dependence on a trusted third party, most PoRs are incapable of achieving essential and straightforward trust between participants (i.e. the client and server). While blockchain shows promise in solving this trust issue, existing blockchain-based storage systems are scenario-constrained as they require private/permissioned or special-construct blockchains. Consequently, none of these systems provide robust and decentralized trustworthiness. We propose a general Blockchain-based Automatic Audit (BAA) scheme for PoR without limitations based on specific blockchain types. Specifically, we present BAA via stitching together a carefully designed or chosen array of sub-components such as storage proofs and Turing-complete smart contracts. We also integrate BAA with specific PoR models to prove its strong generality and availability. To our best knowledge, our proposal is the first blockchain-based approach that enhances traditional PoR models with both automatic audit and fair payment. The final analysis and implemented prototype on Ethereum demonstrate the utility of BAA.

A Blockchain-Based Privacy-Preserving and Fair Data Transaction Model in IoT

The rapid development of the Internet of Things (IoT) has resulted in vast amounts of widely distributed data. Sharing these data can spur innovative advancements and enhance service quality. However, conventional data-sharing methods often involve third-party intermediaries, posing risks of single-point failures and privacy leaks. Moreover, these traditional sharing methods lack a secure transaction model to compensate for data sharing, which makes ensuring fair payment between data consumers and providers challenging. Blockchain, as a decentralized, secure, and trustworthy distributed ledger, offers a novel solution for data sharing. Nevertheless, since all nodes on the blockchain can access on-chain data, data privacy is inadequately protected, and traditional privacy-preserving methods like anonymization and generalization are ineffective against attackers with background knowledge. To address these issues, this paper proposes a decentralized, privacy-preserving, and fair data transaction model based on blockchain technology. We designed an adaptive local differential privacy algorithm, MDLDP, to protect the privacy of transaction data. Concurrently, verifiable encrypted signatures are employed to address the issue of fair payment during the data transaction process. This model proposes a committee structure to replace the individual arbitrator commonly seen in traditional verifiable encrypted signatures, thereby reducing potential collusion between dishonest traders and the arbitrator. The arbitration committee leverages threshold signature techniques to manage arbitration private keys. A full arbitration private key can only be collaboratively constructed by any arbitrary t members, ensuring the key’s security. Theoretical analyses and experimental results reveal that, in comparison to existing approaches, our model delivers enhanced transactional security. Moreover, while guaranteeing data availability, MDLDP affords elevated privacy protection.

Attribute Based Conjunctive Keywords Search With Verifiability and Fair Payment Using Blockchain

Attribute Based Conjunctive Keywords Search With Verifiability and Fair Payment Using Blockchain

Exploring macro-environmental factors influencing adoption of result-based and collective agri-environmental measures: a PESTLE approach based on stakeholder statements

To promote more environmentally friendly and cost-effective agri-environmental-climate measures in the European Union, novel approaches such as result-based and collective schemes are advocated. This study explores macro-environmental factors facilitating or impeding the adoption of such schemes. By means of a PESTLE analysis and based on a survey of 85 stakeholders from Austria and Germany, we identify major adoption factors within the political, economic, social, technological, legal, and environmental domains. Our results indicate that economic, legal, and social factors are the most influential, with fair payment, clear contract design, and social relations being the most commonly mentioned. Moreover, the unpredictability of nature is a major impediment to the adoption of result-based schemes, while social dynamics and farmers’ attitudes are key factors for a successful implementation of collective contracts. Overall, the study provides strategic and practical insights that can support the design and implementation of novel agri-environmental-climate measures under the Common Agricultural Policy.

Bpf-payment: Fair payment for cloud computing with privacy based on blockchain and homomorphic encryption

Bpf-payment: Fair payment for cloud computing with privacy based on blockchain and homomorphic encryption

Smart contract-based integrity audit method for IoT

With the widespread adoption of Internet of Things (IoT) technology, a large amount of private data has been generated. Due to the limited computing and storage resources of IoT devices, enterprises and individuals choose to use a cloud storage provider (CSP) to manage their data. However, they lose the actual control of the data, and hence users need to verify the integrity of the data in the cloud. As a result, reducing the computational overhead of integrity auditing tasks for massive amounts of data and optimizing the distribution of benefits among the participants have become the key to the healthy development of IoT technologies. This paper proposes an integrity auditing method based on smart contracts. First, we construct a noninteractive auditing model based on a chaotic system so that the third-party auditor (TPA) can complete the auditing task without challenging the CSP. Second, we proposed a new construction method for audit trees that can quickly generate the verification tag of the root node. Finally, we design a smart contract-based auditing algorithm on the blockchain, which can simultaneously verify the behaviour of the CSP and the TPA to achieve fair payments. The theoretical analysis shows that our scheme can effectively prevent the TPA from falsifying audit results and prevent collusion between the TPA and the CSP. The experimental results show that our scheme has higher audit efficiency.

Next-power: Next-generation framework for secure and sustainable energy trading in the metaverse

The rapid emergence of the Metaverse as a leading virtual digital technology is driving innovation in power generation. The increasing demand for sustainable energy and the rise of the Metaverse has provided an opportunity to develop a secure and sustainable energy trading system using Smart Grid (SG), Virtual Power Plants (VPP), Digital Twins (DT), and Blockchain. Integrating VPP with SG can optimize the utilization of distributed energy resources and improve the stability and reliability of the energy supply in the metaverse. Meanwhile, the use of DT can facilitate the efficient management of VPPs by simulating their behavior and performance to identify potential issues and test different scenarios for improvement. Blockchain is a rising technology that enables decentralized and trustworthy applications, making it a promising tool for creating decentralized energy trading systems in the Metaverse. In this context, we propose Next-Power, a next-generation framework for secure and sustainable energy trading in the Metaverse. Next-Power consists of: (1) an automated blockchain-based fair payment of energy traded between consumers and prosumers in the Metaverse, it uses Ethereum’s smart contracts to determine the price at which energy is traded using a cooperative game theory (i.e., reverse auction); (2) an access token-based blockchain system that ensures a secure mutual authentication between consumers and prosumers; and (3) a lightweight on-chain collaborative reputation scheme that keeps track of prosumers reputation as well as consumers credibility in the Metaverse in a fully decentralized manner. The system of Next-Power is implemented, tested, and deployed on the Ethereum official test network. Next-Power is a promising framework for the future of energy trading in the Metaverse, as demonstrated by its successful experimental results in terms of flexibility, efficiency, security, and cost-effectiveness.

Blockchain-based decentralized supply chain system with secure information sharing

Supply chain management (SCM) has become an important way for the companies to improve the production efficiency and reduce the management cost. However, the existing SCM system is usually built and performed with the semi-trusted certificate authority, which may be susceptible to the collusion attack and tampering attack launched by the malicious certificate authority, resulting in illegal modification of product provenance record. Moreover, the lack of transparent and mutual trust among the stakeholders in the SCM system remains a great challenging issue. In this paper, we propose a blockchain-based decentralized supply chain system with secure information sharing, which can ensure the security of product provenance record without relying on any fully trusted intermediary. In our system, two validation mechanisms, i.e., one-way validation mechanism and transaction-based validation mechanism are built to help the stakeholders to perform the validation of product provenance record without accessing their original content. Furthermore, the blockchain-based smart contract is used to achieve secure registration, proper authentication and fair payment for all stakeholders, where the valid stakeholders can pay for the purchased products, automatically and reliably. Security analysis and performance evaluation demonstrate that our proposed scheme is secure, feasible and efficient with a limited and reasonable computation cost.

PRI: PCH-based privacy-preserving with reusability and interoperability for enhancing blockchain scalability

Blockchain systems, one of the most popular distributed systems, are well-applied in various scenarios, e.g., logistics and finance. However, traditional blockchain systems suffer from scalability issues. To tackle this issue, Payment Channel Hubs (PCHs) are proposed. Recent efforts, such as A2L (SP'21) and Teechain (SOSP'19), enhance the privacy, reusability, and interoperability properties of PCHs. Nevertheless, these solutions have intrinsic limitations: they rely on trusted hardware or suffer from the deposit lock-in problem. Furthermore, the functionalities of some of these solutions are restricted to fixed-amount payments and do not support multi-party participation. These aforementioned problems limit their capabilities to alleviate blockchain scalability issues. In this paper, we propose PRI, a novel PCH solution that simultaneously guarantees transaction Privacy (i.e., relationship unlinkability and value confidentiality), deposit Reusability, and blockchain Interoperability, which can mitigate the aforementioned problems. PRI is constructed by several new building blocks, including (1) an atomic deposit protocol that enforces user and hub to deposit equivalent assets in a shared address for building a fair payment channel; (2) a privacy-preserving deposit certification scheme that leverages the Pointcheval and Sanders signature and non-interactive zero-knowledge proof to resolve the deposit lock-in issue in maintaining payment channels; (3) a range proof which ensures the legality and confidentiality of transaction values. We conduct extensive experimental evaluations of PRI, demonstrating that it improves the state-of-the-art approaches in terms of performance.