Reputation Incentive Mechanism Research Articles

Unveiling the impact of E-commerce on smallholder livestock marketing: Insights on egg price premiums and mechanisms

The rise of e-commerce is essentially transforming the landscape of agri-food marketing. E-commerce platforms offer smallholder farmers unparalleled access to markets for their distinct products. This study investigates this transformative impact by using egg trading data sourced from a prominent Chinese platform. We focus on the empowering dynamics and mechanisms of e-commerce within smallholder livestock marketing, particularly concerning price premiums. Utilizing a hedonic pricing model, we investigate two potential pathways that likely stimulate smallholder livestock sales in the online platforms: the information display mechanism and the reputation incentive mechanism. Our study identifies the smallholder attribute that drive price premiums for eggs. We explain how these mechanisms influence the augmentation of price premiums about the smallholder attribute. First, e-commerce plays a pivotal role in bolstering the perception of consuming value through the information display mechanism. Second, the reputation incentives foster a sense of trust in consuming quality by accumulating empirical evaluation feedback from consumers. Our findings highlight the critical role of advancing e-commerce development in linking markets to smallholder farmers.

A scalable, efficient, and secured consensus mechanism for Vehicle-to-Vehicle energy trading blockchain

Vehicle-to-Vehicle (V2V) energy trading has emerged as a promising scheme to relieve the load imposed on the grid without intermediaries. The blockchain has always been regarded as the most potential solution for addressing the security and privacy issues of the Internet of Electric Vehicles (IoEV). The consensus mechanism is the core of the blockchain, it determines the security, efficiency, and scalability of the system. However, consensus mechanisms currently employed in V2V energy trading are traditional algorithms, which are unsuitable for the IoEV due to their high computational power and communication overhead. Therefore, we are motivated to propose a Block Alliance Consensus (BAC) mechanism based on Hashgraph. BAC can maintain the high throughput of the Hashgraph, and it solves the problem that the Hashgraph cannot support the dynamic addition and deletion of nodes if it is directly applied to V2V energy trading. We utilize the sharding technique, and each shard generates a consortium blockchain in accordance with the characteristic of the IoEV. The centralized component is retained to ensure macroeconomic control by state and local governments. We design a cryptography-based leader election combined with a reputation incentive mechanism to fairly elect centralized leader committee and motivate honest electric vehicles (EVs). We implement the BAC consensus and V2V energy trading blockchain (ETB) on the Hyperledger Fabric. The performance and practicality of BAC and the V2V ETB are verified through experiments.

A Fast and Secured Vehicle-to-Vehicle Energy Trading Based on Blockchain Consensus in the Internet of Electric Vehicles

The organization and management of electricity markets worldwide are rapidly evolving, moving towards decentralized, distributed, and renewable energy-based generation with solutions based on real-time data exchange. A Vehicle-to-Vehicle (V2V) energy trading has emerged as one of the most promising alternatives for relieving the load imposed on the traditional grid enabling two individuals to buy and sell energy directly without intermediaries. However, the Internet of Electric Vehicles (IoEV) environment is trustless, and such P2P energy trading is prone to different kinds of cyber attacks. Blockchain technology has lately been proposed to implement V2V energy trading to securely and fairly share energy. The consensus mechanism is one of the most important modules of blockchain applied to the V2V network. It determines the efficiency and security among untrustworthy EVs of the energy trading blockchain (ETB). Nevertheless, most works on ETB have currently adopted traditional consensus mechanisms. Due to high computing power and communication overhead, these consensus algorithms are unsuitable for applications requiring real-time services such as energy trading. The efficient and secured Hashgraph is the revolutionary technology of consensus in blockchain and a promising technology suitable for V2V energy trading with frequent transactions. However, Hashgraph does not support the dynamic addition and deletion of nodes and is completely decentralized and vulnerable to Sybil Attack in a large-scale blockchain. Furthermore, this “complete decentralization” model may result in states losing the ability to macro-control the energy industry and even systemic energy security issues. Therefore, we propose a Block Alliance Consensus (BAC) mechanism to solve these problems. BAC can maintain the throughput of Hashgraph and resist Sybil Attack in a large-scale P2P energy trading network. We design a cryptography-based leader election mechanism and adopt a reputation incentive mechanism to motivate honest and cooperative electric vehicles (EVs). Finally, we implement ETB and the BAC consensus mechanism on the Hyperledger Fabric platform. The high efficiency and security of BAC and the blockchain-based V2V energy trading platform are verified through experiments.

A Game-Theoretical Approach for Secure Crowdsourcing-Based Indoor Navigation System With Reputation Mechanism

At present, the crowdsourcing-based indoor navigation system (CINS) has attracted extensive attention from both industry and academia owing to its low-cost and high-accuracy performance. Unfortunately, the system that relies on crowdsourced data is vulnerable to the collusion attack, which leads to severe security issues. To address the security issues in the CINS, we propose to utilize a fully trusted fog server platform to advocate secure transactions between service requesters and responders. First, we propose a novel reputation incentive mechanism based on the behaviors of responders. Then, we employ the offensive and defensive game to model the interactions between the fog server platform and the responders, whereby a social welfare optimization problem is formulated to maximize the social welfare of the system. Next, the game equilibriums are found by using the replicator dynamic equation while the game stability is discussed. Finally, the simulation results show that the proposed mechanism can effectively encourage responders to provide positive navigation services and obtain more social welfare of the system compared with the conventional mechanisms.

Design of Teaching Material Evaluation Incentive Mechanism based on Game Theory

As the carrier of knowledge and the basis of teaching, teaching materials affect the teaching quality of schools. However, the selection of teaching materials in colleges and universities is in a dilemma because of the variety of teaching materials and the uneven quality of teaching materials. Blockchain has gradually drawn attention from various fields, due to its secure storage, non-forgery and non-tamper features. The combination of blockchain and teaching material evaluation can provide fair and transparent grading and evaluation for teaching materials, which is of great reference value for colleges and universities to select teaching materials. This paper proposes a reputation incentive mechanism for teaching material evaluation blockchain based on game theory, analyzes the behavior of users in the scoring stage of teaching material evaluation, and gives the Nash equilibrium solution. Through the numerical simulation experiment, the effectiveness of the incentive mechanism and the reliability of the teaching materials’ evaluation results are proved.

A Data Sharing Scheme for GDPR-Compliance Based on Consortium Blockchain

After the General Data Protection Regulation (GDPR) was introduced, some organizations and big data companies shared data without conducting any privacy protection and compliance authentication, which endangered user data security, and were punished financially for this reason. This study proposes a blockchain-based GDPR compliance data sharing scheme, aiming to promote compliance with regulations and provide a tool for interaction between users and service providers to achieve data security sharing. The zero-knowledge Succinct Non-Interactive Arguments of Knowledge (zk-SNARK) algorithm is adopted for protecting data and ensure that the user’s private data can satisfy the individual requirements of the service provider without exposing user data. The proposed scheme ensures mutual authentication through the Proof of Authority consensus based on the Committee Endorsement Mechanism (CEM-PoA), and prevents nodes from doing evil using the reputation incentive mechanism. Theoretical analysis and performance comparison indicate that the scheme meets the confidentiality, availability, and other indicators. It has superiority in efficiency and privacy protection compared with other schemes.

Futuristic blockchain based scalable and cost-effective 5G vehicular network architecture

In the present era, smart and efficient vehicular network architectures are necessary due to fast technological advancements in vehicles. Many problems arise in these complex networks, which can be handled using blockchain and the Internet of Things (IoT). We proposed a comprehensive blockchain based 5G vehicular network architecture, which is cost-effective, scalable, secure, and handles various vehicular network issues in a smart city. The proposed architecture consists of all essential components like reputation system, incentive mechanism, and priority based techniques to handle different limitations in the literature. Simulations results for different scenarios depict the high execution cost of a single controller node, minor node, and ordinary node as 106305, 85864, and 65491 gas values and transaction cost as 130521, 109824, and 89195 gas values. The results depict the effectiveness of the proposed architecture in terms of scalability, time and cost-effectiveness.

网络学习空间中的声誉激励机制——基于学习者视角

网络学习空间中的声誉激励机制——基于学习者视角

Mining and Construction of Information Opportunity Cooperation Mode Based on Big Data Fusion Internet of Things

This paper introduces evolutionary game theory as an analysis tool to study the evolution of the cooperative behavior of nodes in the opportunistic network. At the same time, considering the spatial distribution of nodes in the opportunistic network and the corresponding cooperative interaction relationship, the evolutionary graph theory is further applied to study the cooperative behavior in the context of considering the network space. In the collaboration model of this article, the vertices in the evolutionary graph theory are used to represent the nodes in the network, and the edges in the graph represent that the node pairs are within the communication range of each other. The node will play a game with neighboring nodes according to the payout matrix. Through repeated games between nodes, the network reaches a relatively stable final state, and the distribution of nodes with different behaviors in the final state of the network is checked. By adjusting the network parameters, we can analyze the distribution and evolution of cooperation in the network, and study the stability of the network. We realize the credible collaborative evolutionary game model by building a comprehensive simulation platform and verify its effectiveness and scalability. We design and implement an evolutionary game model independent of routing protocols, so that the model can be quickly deployed in traditional routing protocols. Subsequently, simulations verified that the reputation model played a role in guiding nodes to actively participate in network collaboration during the collaborative evolution process. And the greater the strength of the reputation incentive mechanism, the better the effect of the evolutionary model. The evolution model is deployed in multiple routing protocols, verifying that the model can play a role in different routing protocols. In addition, the evolution model can also play a role in different network environments and has good scalability.

Consortium Blockchain based Reputation Incentive Mechanism for Recommendation System

Recommendation systems have been widely used in many e-commerce services, but it is difficult to gather enough participants to supply their recommendations. Moreover, participants in the system may make malicious recommendations, which will affect the accuracy of recommendation results. In order to provide better recommendation service for users, incentive mechanisms are needed to attract more participants in recommendation and curb their malicious behaviors. In this paper, we propose a consortium blockchain based reputation incentive mechanism for recommendation systems(CRIM). Firstly, the monetary rewards are used to attract participants and motivate them to take part in the recommendation. Secondly, we design the incentive mechanism with reputation which is attached to the rewards. Honest participants will gain more rewards while malicious participants will be penalized. Meanwhile, we adopt the Stackelberg game to maximize the utility of participants, and prove that the mechanism can reach a unique Nash equilibrium. Thirdly, the decentralization and immutability of blockchain can guarantee the credibility and security of the stored data, thus ensuring the openness and transparency of the recommendation. Finally, we implement the system for education resources recommendation and conduct experiments, and the results demonstrate that our incentive mechanism is effective and has significant performance when compared with other incentive mechanisms.

DE-Sword: Incentivized Verifiable Tag Path Query in RFID-Enabled Supply Chain Systems

In this article, we propose Double Edged (DE)-Sword, an incentivized verifiable tag path query scheme. DE-Sword queries tag records stored across a path of participants within an RFID-enabled supply chain in a verifiable way. Different with previous works, DE-Sword works in a dishonest-data owner model in which participants are the owners of tag records and may be dishonest. DE-Sword introduces a novel double-edged reputation incentive mechanism to encourage participants to behave honestly; and couples it with cryptographic primitives to ensure query verifiability. We evaluate DE-Sword through game theory, security analysis, and performance evaluation. The game theory and security analysis shows that DE-Sword guarantees query verifiability. The evaluation results show that DE-Sword incurs low overhead in supply chain systems.

A novel reputation incentive mechanism and game theory analysis for service caching in software-defined vehicle edge computing

Service caching can improve the QoS of computationally intensive vehicle applications by pre-storing the necessary application programs and related data for computing tasks on edge servers. In this paper, we propose a new vehicle edge computing framework based on software defined networks, which introduces the reputation to measure the contribution of each vehicle as the basis for providing different quality of services. The process is divided into two phases: in the first phase, the vehicle requests the offload application task from the edge server; and in the second phase, the edge server makes the service caching decision after processing the task. We design the whole interaction process as a kind of incentive mechanism based on reputation via using Stackelberg game modeling, and analyze the optimal strategy for both sides of the game by reverse induction. Furthermore, we also prove the existence and uniqueness of Stackelberg equilibrium in two-stage game, and a genetic optimization algorithm is designed to quickly obtain the optimal strategy for both sides of the game. Experimental results show that the proposed scheme not only brings more profits to the edge server side, but also reduces the average delay by 76 % compared with the ordinary mobile edge computing scheme.

Dynamic Reputation Incentive Mechanism for Urban Water Environment Treatment PPP Projects

AbstractNew approaches are provided for urban water environment treatment projects (UWETP) with the development and application of the public-private partnership (PPP) model. However, an asymmetry ...

The research of reputation incentive mechanism of P2P network file sharing system

In the digital information age, data sharing and security are important research topics, data sharing technology and information security technology have developed rapidly. The reputation incentive mechanism based on interest of nodes is important in P2P file sharing system. This mechanism can reduce the transaction risk in P2P file sharing system, improve the success rate of transaction and maintain the sound development of network. In addition, in this paper, two typical security problems (naive attack and sybil attack) are studied to minimise the damage to the network. The simulation and analysis of the success rate of resource location and transaction show that the reputation incentive mechanism is correct, feasible and effective. Furthermore, it has significant improvements in security and simplicity.

The research of reputation incentive mechanism of P2P network file sharing system

In the digital information age, data sharing and security are important research topics, data sharing technology and information security technology have developed rapidly. The reputation incentive mechanism based on interest of nodes is important in P2P file sharing system. This mechanism can reduce the transaction risk in P2P file sharing system, improve the success rate of transaction and maintain the sound development of network. In addition, in this paper, two typical security problems (naive attack and sybil attack) are studied to minimise the damage to the network. The simulation and analysis of the success rate of resource location and transaction show that the reputation incentive mechanism is correct, feasible and effective. Furthermore, it has significant improvements in security and simplicity.

DDOA: A Dirichlet-Based Detection Scheme for Opportunistic Attacks in Smart Grid Cyber-Physical System

In the hierarchical control paradigm of a smart grid cyber-physical system, decentralized local agents (LAs) can potentially be compromised by opportunistic attackers to manipulate electricity prices for illicit financial gains. In this paper, to address such opportunistic attacks, we propose a Dirichlet-based detection scheme, where a Dirichlet-based probabilistic model is built to assess the reputation levels of LAs. Initial reputation levels of the LAs are first trained using the proposed model, based on their historical operating observations. An adaptive detection algorithm with reputation incentive mechanism is then employed to detect opportunistic attackers. We demonstrate the utility of our proposed scheme using data collected from the IEEE 39-bus power system with the PowerWorld simulator.

Study on the Quality Control of Reputation-Based on Incentive Service-Oriented Manufacturing Network

Manufacturing enterprises, manufacturing services and customer constitute the service-oriented manufacturing dynamic network (SMN). The quality of SMN mainly depends on the service module provider. Under the condition of information asymmetry in the market, service module provider pursuits for self-interest maximization, may take quality speculation. Based on the reputation incentive theory, this paper establishes an optimal SMN node quality behavior dynamic model of the contract which combines with dominant incentive mechanism and reputation incentive mechanism, discusses the factors which influence the service module provider’s effort level, the conditions of realizing effective reputation incentive and the ways to improve reputation incentive effect.

A P2P Reputation Incentive Mechanism based on Artificial Fish-Swarm Model

Recently, P2P networks play an important role in network. However, there exist a large amount of malicious actions in P2P networks resulting from the lack of reputation system. For example, nodes are willing to share resources each other and may withdraw from networks at any time. Thus, the system is difficult to guarantee effectiveness and availability. According to the behavior of fish school, A novel optimizing, Fish-swam Algorithm, was proposed in this paper, which can decide the next step when nodes have no interactive experience with others. The algorithm based on the model of autonoms animals and was presented to be a kind of efficient incentive mechanism, through a series of experimental study.

Reputation incentive mechanism based on dynamic topology

In order to increase the rate of successful exchange,encourage peers to contribute their recourses actively,and make the P2P file sharing system develop continually,a dynamic topology based reputation was proposed.The peers in the P2P network were encouraged to contribute their recourses via the incentive mechanism,so the network would be running continually.These made P2P file sharing system work normally,and the capability of network would be increased.The simulation experiments and theoretical analysis of the reputation incentive mechanism prove that the mechanism is correct and valid.Compared with the former trust models,the reputation incentive mechanism has higher security and simplicity,and reaches the expected goal.

Study on reputation incentive effect of environmental pollution control in scenic area

The information asymmetries between scenic area and tourists and between scenic area and tourism management department have made it more difficult to conduct pollution control in scenic area, and even made the scenic area to evade responsibilities of pollution control intentionally or unintentionally. On the basis of reputation model, this paper discusses the effective equilibrium conditions of reputation incentive mechanism under asymmetric information through analysing the generating process of reputation incentive effect during scenic area pollution control. And then based on the discussion, some policies to improve the initiative of pollution control in scenic area are suggested.