In order to identify plants and recipes used in the treatment of malaria in Bagira,an ethnobotanical study was conducted from December 2013 to February 2014,by interviewing 85 traditional healers(46.9±12.0 averag...In order to identify plants and recipes used in the treatment of malaria in Bagira,an ethnobotanical study was conducted from December 2013 to February 2014,by interviewing 85 traditional healers(46.9±12.0 average age;range:19-79 years).The direct interview using a questionnaire was used to collect ethnobotanical information.A specimen of each plant was collected展开更多
Purpose:For a set of 1,561 Open Access(OA)and non-OA journals in business and economics,this study evaluates the relationships between four citation metrics-five-year Impact Factor(5IF),CiteScore,Article Influence(AI)...Purpose:For a set of 1,561 Open Access(OA)and non-OA journals in business and economics,this study evaluates the relationships between four citation metrics-five-year Impact Factor(5IF),CiteScore,Article Influence(AI)score,and SCImago Journal Rank(SJR)-and the journal ratings assigned by expert reviewers.We expect that the OA journals will have especially high citation impact relative to their perceived quality(reputation).Design/methodology/approach:Regression is used to estimate the ratings assigned by expert reviewers for the 2021 CABS(Chartered Association of Business Schools)journal assessment exercise.The independent variables are the four citation metrics,evaluated separately,and a dummy variable representing the OA/non-OA status of each journal.Findings:Regardless of the citation metric used,OA journals in business and economics have especially high citation impact relative to their perceived quality(reputation).That is,they have especially low perceived quality(reputation)relative to their citation impact.Research limitations:These results are specific to the CABS journal ratings and the four citation metrics.However,there is strong evidence that CABS is closely related to several other expert ratings,and that 5IF,CiteScore,AI,and SJR are representative of the other citation metrics that might have been chosen.Practical implications:There are at least two possible explanations for these results:(1)expert evaluators are biased against OA journals,and(2)OA journals have especially high citation impact due to their increased accessibility.Although this study does not allow us to determine which of these explanations are supported,the results suggest that authors should consider publishing in OA journals whenever overall readership and citation impact are more important than journal reputation within a particular field.Moreover,the OA coefficients provide a useful indicator of the extent to which anti-OA bias(or the citation advantage of OA journals)is diminishing over time.Originality/value:This is apparently the first study to investigate the impact of OA status on the relationships between expert journal ratings and journal citation metrics.展开更多
In response to the challenges presented by the unreliable identity of the master node,high communication overhead,and limited network support size within the Practical Byzantine Fault-Tolerant(PBFT)algorithm for conso...In response to the challenges presented by the unreliable identity of the master node,high communication overhead,and limited network support size within the Practical Byzantine Fault-Tolerant(PBFT)algorithm for consortium chains,we propose an improved PBFT algorithm based on XGBoost grouping called XG-PBFT in this paper.XG-PBFT constructs a dataset by training important parameters that affect node performance,which are used as classification indexes for nodes.The XGBoost algorithm then is employed to train the dataset,and nodes joining the system will be grouped according to the trained grouping model.Among them,the nodes with higher parameter indexes will be assigned to the consensus group to participate in the consensus,and the rest of the nodes will be assigned to the general group to receive the consensus results.In order to reduce the resource waste of the system,XG-PBFT optimizes the consensus protocol for the problem of high complexity of PBFT communication.Finally,we evaluate the performance of XG-PBFT.The experimental results show that XG-PBFT can significantly improve the performance of throughput,consensus delay and communication complexity compared to the original PBFT algorithm,and the performance enhancement is significant compared to other algorithms in the case of a larger number of nodes.The results demonstrate that the XG-PBFT algorithm is more suitable for large-scale consortium chains.展开更多
Blockchain-based user-centric access network(UCAN)fails in dynamic access point(AP)management,as it lacks an incentive mechanism to promote virtuous behavior.Furthermore,the low throughput of the blockchain has been a...Blockchain-based user-centric access network(UCAN)fails in dynamic access point(AP)management,as it lacks an incentive mechanism to promote virtuous behavior.Furthermore,the low throughput of the blockchain has been a bottleneck to the widespread adoption of UCAN in 6G.In this paper,we propose Overlap Shard,a blockchain framework based on a novel reputation voting(RV)scheme,to dynamically manage the APs in UCAN.AP nodes in UCAN are distributed across multiple shards based on the RV scheme.That is,nodes with good reputation(virtuous behavior)are likely to be selected in the overlap shard.The RV mechanism ensures the security of UCAN because most APs adopt virtuous behaviors.Furthermore,to improve the efficiency of the Overlap Shard,we reduce cross-shard transactions by introducing core nodes.Specifically,a few nodes are overlapped in different shards,which can directly process the transactions in two shards instead of crossshard transactions.This greatly increases the speed of transactions between shards and thus the throughput of the overlap shard.The experiments show that the throughput of the overlap shard is about 2.5 times that of the non-sharded blockchain.展开更多
Taking China’s 2018 value-added tax(VAT)credit refund reform as an exogenous shock to improve VAT neutrality,we use a difference-in-differences approach to explore how the reform affected corporate social responsibil...Taking China’s 2018 value-added tax(VAT)credit refund reform as an exogenous shock to improve VAT neutrality,we use a difference-in-differences approach to explore how the reform affected corporate social responsibility(CSR).We find that the reform motivated firms to improve CSR performance.The reform has a“resource”effect,increasing internal funds and reducing financing costs,thereby enhancing firms’ability to undertake CSR.The reform also has a“reputation”effect,stimulating firms’willingness to engage in CSR to improve their reputations.CSR following the reform increases firm values and reduces bankruptcy risk.Our study provides fresh insights into VAT neutrality theory and is a reference for tax reform in emerging economies.展开更多
With the development of vehicle networks and the construction of roadside units,Vehicular Ad Hoc Networks(VANETs)are increasingly promoting cooperative computing patterns among vehicles.Vehicular edge computing(VEC)of...With the development of vehicle networks and the construction of roadside units,Vehicular Ad Hoc Networks(VANETs)are increasingly promoting cooperative computing patterns among vehicles.Vehicular edge computing(VEC)offers an effective solution to mitigate resource constraints by enabling task offloading to edge cloud infrastructure,thereby reducing the computational burden on connected vehicles.However,this sharing-based and distributed computing paradigm necessitates ensuring the credibility and reliability of various computation nodes.Existing vehicular edge computing platforms have not adequately considered themisbehavior of vehicles.We propose a practical task offloading algorithm based on reputation assessment to address the task offloading problem in vehicular edge computing under an unreliable environment.This approach integrates deep reinforcement learning and reputation management to address task offloading challenges.Simulation experiments conducted using Veins demonstrate the feasibility and effectiveness of the proposed method.展开更多
Aim To study the implicit restriction mechanism for hidden action in multi stage dynamic game. Methods A reputation model for restriction on repeated principal agent relationship was established by using the theor...Aim To study the implicit restriction mechanism for hidden action in multi stage dynamic game. Methods A reputation model for restriction on repeated principal agent relationship was established by using the theory on principal agent problem in information economics and the method of game theory to study the implicit restriction mechanism for hidden action. Results and Conclusion It is proved that there exists implicit restriction mechanism for the multi stage principal agent relationship, some conditions for effective restriction are derived, the design methods of implicit restriction mechanism are presented.展开更多
Is He Living or Is He Dead is mainly about an outstanding painter Francois Millet who pretend to be dead in order to get reputation and money,because at that time a great artist has never been acknowledged until after...Is He Living or Is He Dead is mainly about an outstanding painter Francois Millet who pretend to be dead in order to get reputation and money,because at that time a great artist has never been acknowledged until after he was starved and dead. Based on the critic approach of New Historicism, this thesis have analyzed how Millet subvert power and be contained by power, the capitalism and market, which criticized the phenomenon that the value of art is not decided by itself, but by power. No matter it is good or bad, if it is denied by power, it is valueless.展开更多
Bitcoin has a bad reputation.The decentralised digital cryptocurrency,powered by a vast computer network,is notorious for the wild fluctuations in its value,the zeal of its supporters and its degenerate uses,such as e...Bitcoin has a bad reputation.The decentralised digital cryptocurrency,powered by a vast computer network,is notorious for the wild fluctuations in its value,the zeal of its supporters and its degenerate uses,such as extortion,buying drugs and hiring hitmen in the online bazaars of the'dark net'.比特币有一个坏名声。这种由一个庞大的计算机网络来驱动的去中心化数字加密货币,其恶名源于币值的剧烈波动、支持者的狂热追捧以及各种堕落的用途,如敲诈勒索、购买毒品和在'暗网'的在线市场雇佣杀手等。展开更多
As an emerging distributed technology, blockchain has begun to penetrate into many fields such as finance, healthcare, supply chain, intelligent transportation. However, the interoperability and value exchange between...As an emerging distributed technology, blockchain has begun to penetrate into many fields such as finance, healthcare, supply chain, intelligent transportation. However, the interoperability and value exchange between different independent blockchain systems is restricting the expansion of blockchain. In this paper, a notary group-based cross-chain interaction model is proposed to achieve the interoperability between different blockchains. Firstly, a notary election mechanism is proposed to choose one notary from the notary group to act as a bridge for cross-chain transactions. Secondly, a margin pool is introduced to limit the misconduct of the elected notary and ensure the value transfer between the involved blockchains. Moreover, a reputation based incentive mechanism is used to encourage members of the notary group to participate in cross-chain transactions. Ethereum-based experiments demonstrate that the proposed mechanism can provide an acceptable performance for cross-chain transactions and provide a higher security level than ordinary cross-chain mechanisms.展开更多
MANET routing is critical and routing decision should be made sooner before the node leaves the network.Fast decisions always compensate network performance.In addition,most MANET routing protocols assume a friendly a...MANET routing is critical and routing decision should be made sooner before the node leaves the network.Fast decisions always compensate network performance.In addition,most MANET routing protocols assume a friendly and cooperative environment,and hence are vulnerable to various attacks.Trust and Reputation would serve as a major solution to these problems.Learning the network characteristics and choosing right routing decisions at right times would be a significant solution.In this work,we have done an extensive survey of fault tolerant protocols and ant colony algorithms applied to routing in MANETs.We propose a QoS constrained fault tolerant ant lookahead routing algorithm which attempts to identify valid route and look-ahead route pairs which might help in choosing the alternate path in case of valid route failure.The results prove that the proposed algorithm takes better routing decisions with 20-30 percent improvement compared with existing ant colony algorithms.展开更多
A Service Level Agreement(SLA) is a legal contract between any two parties to ensure an adequate Quality of Service(Qo S). Most research on SLAs has concentrated on protecting the user data through encryption. However...A Service Level Agreement(SLA) is a legal contract between any two parties to ensure an adequate Quality of Service(Qo S). Most research on SLAs has concentrated on protecting the user data through encryption. However, these methods can not supervise a cloud service provider(CSP) directly. In order to address this problem, we propose a privacy-based SLA violation detection model for cloud computing based on Markov decision process theory. This model can recognize and regulate CSP's actions based on specific requirements of various users. Additionally, the model could make effective evaluation to the credibility of CSP, and can monitor events that user privacy is violated. Experiments and analysis indicate that the violation detection model can achieve good results in both the algorithm's convergence and prediction effect.展开更多
Wireless Mesh Networks （WMNs） are vulnerable to various security threats because of their special infrastructure and communication mode, wherein insider attacks are the most challenging issue. To address this proble...Wireless Mesh Networks （WMNs） are vulnerable to various security threats because of their special infrastructure and communication mode, wherein insider attacks are the most challenging issue. To address this problem and protect innocent users from malicious attacks, it is important to encourage cooperation and deter malicious behaviors. Reputation systems constitute a major category of techniques used for managing trust in distributed networks, and they are effective in characterizing and quantifying a node＇s behavior for WMNs. However, conventional layered reputation mechanisms ignore several key factors of reputation in other layers; therefore, they cannot provide optimal performance and accurate malicious node identification and isolation for WMNs. In this paper, we propose a novel dynamic reputation mechanism, SLCRM, which couples reputation systems with a cross-layer design and node-security-rating classification techniques to dynamically detect and restrict insider attacks. Simulation results show that in terms of network throughput, packet delivery ratio, malicious nodes＇ identification, and success rates, SI_CRM imple- ments security protection against insider attacks in a more dynamic, effective, and efficient manner than the subjective logic and uncertainty-based reputation model and the familiarity-based reputation model.展开更多
Volunteered geographic information(VGI)has entered a phase where there are both a substantial amount of crowdsourced information available and a big interest in using it by organizations.But the issue of deciding the ...Volunteered geographic information(VGI)has entered a phase where there are both a substantial amount of crowdsourced information available and a big interest in using it by organizations.But the issue of deciding the quality of VGI without resorting to a comparison with authoritative data remains an open challenge.This article first formulates the problem of quality assessment of VGI data.Then presents a model to measure trustworthiness of information and reputation of contributors by analyzing geometric,qualitative,and semantic aspects of edits over time.An implementation of the model is running on a small data-set for a preliminary empirical validation.The results indicate that the computed trustworthiness provides a valid approximation of VGI quality.展开更多
In the last few years, cloud computing as a new computing paradigm has gone through significant development, but it is also facing many problems. One of them is the cloud service selection problem. As increasingly boo...In the last few years, cloud computing as a new computing paradigm has gone through significant development, but it is also facing many problems. One of them is the cloud service selection problem. As increasingly boosting cloud services are offered through the internet and some of them may be not reliable or even malicious, how to select trustworthy cloud services for cloud users is a big challenge. In this paper, we propose a multi-dimensional trust-aware cloud service selection mechanism based on evidential reasoning(ER) approach that integrates both perception-based trust value and reputation based trust value, which are derived from direct and indirect trust evidence respectively, to identify trustworthy services. Here, multi-dimensional trust evidence, which reflects the trustworthiness of cloud services from different aspects, is elicited in the form of historical users feedback ratings. Then, the ER approach is applied to aggregate the multi-dimensional trust ratings to obtain the real-time trust value and select the most trustworthy cloud service of certain type for the active users. Finally, the fresh feedback from the active users will update the trust evidence for other service users in the future.展开更多
Users on the Internet usually require venues to provide better purchasing recommendations.This can be provided by a reputation system that processes ratings to provide recommendations.The rating aggregation process is...Users on the Internet usually require venues to provide better purchasing recommendations.This can be provided by a reputation system that processes ratings to provide recommendations.The rating aggregation process is a main part of reputation systems to produce global opinions about the product quality.Naive methods that are frequently used do not consider consumer profiles in their calculations and cannot discover unfair ratings and trends emerging in new ratings.Other sophisticated rating aggregation methods that use a weighted average technique focus on one or a few aspects of consumers′profile data.This paper proposes a new reputation system using machine learning to predict reliability of consumers from their profile.In particular,we construct a new consumer profile dataset by extracting a set of factors that have a great impact on consumer reliability,which serve as an input to machine learning algorithms.The predicted weight is then integrated with a weighted average method to compute product reputation score.The proposed model has been evaluated over three Movie Lens benchmarking datasets,using 10-folds cross validation.Furthermore,the performance of the proposed model has been compared to previous published rating aggregation models.The obtained results were promising which suggest that the proposed approach could be a potential solution for reputation systems.The results of the comparison demonstrated the accuracy of our models.Finally,the proposed approach can be integrated with online recommendation systems to provide better purchasing recommendations and facilitate user experience on online shopping markets.展开更多
The purpose of the next internet of things(Io T)is that of making available myriad of services to people by high sensing intelligent devices capable of reasoning and real time acting.The convergence of Io T and multi-...The purpose of the next internet of things(Io T)is that of making available myriad of services to people by high sensing intelligent devices capable of reasoning and real time acting.The convergence of Io T and multi-agent systems(MAS)provides the opportunity to benefit from the social attitude of agents in order to perform machine-to-machine(M2 M)cooperation among smart entities.However,the selection of reliable partners for cooperation represents a hard task in a mobile and federated context,especially because the trustworthiness of devices is largely unreferenced.The issues discussed above can be synthesized by recalling the well known concept of social resilience in Io T systems,i.e.,the capability of an Io T network to resist to possible attacks by malicious agent that potentially could infect large areas of the network,spamming unreliable information and/or assuming unfair behaviors.In this sense,social resilience is devoted to face malicious activities of software agents in their social interactions,and do not deal with the correct working of the sensors and other information devices.In this setting,the use of a reputation model can be a practicable and effective solution to form local communities of agents on the basis of their social capabilities.In this paper,we propose a framework for agents operating in an Io T environment,called Res Io T,where the formation of communities for collaborative purposes is performed on the basis of agent reputation.In order to validate our approach,we performed an experimental campaign by means of a simulated framework,which allowed us to verify that,by our approach,devices have not any economic convenience to performs misleading behaviors.Moreover,further experimental results have shown that our approach is able to detect the nature of the active agents in the systems(i.e.,honest and malicious),with an accuracy of not less than 11%compared to the best competitor tested and highlighting a high resilience with respect to some malicious activities.展开更多
In recent years,Blockchain is gaining prominence as a hot topic in academic research.However,the consensus mechanism of blockchain has been criticized in terms of energy consumption and performance.Although Proof-of-A...In recent years,Blockchain is gaining prominence as a hot topic in academic research.However,the consensus mechanism of blockchain has been criticized in terms of energy consumption and performance.Although Proof-of-Authority(PoA)consensus mechanism,as a lightweight consensus mechanism,is more efficient than traditional Proof-of-Work(PoW)and Proof-of-Stake(PoS),it suffers from the problem of centralization.To this end,on account of analyzing the shortcomings of existing consensus mechanisms,this paper proposes a dynamic reputation-based consensus mechanism for blockchain.This scheme allows nodes with reputation value higher than a threshold apply to become a monitoring node,which can monitor the behavior of validators in case that validators with excessive power cause harm to the blockchain network.At the same time,the reputation evaluation algorithm is also introduced to select nodes with high reputation to become validators in the network,thus increasing the cost of malicious behavior.In each consensus cycle,validators and monitoring nodes are dynamically updated according to the reputation value.Through security analysis,it is demonstrated that the scheme can resist the attacks of malicious nodes in the blockchain network.By simulation experiments and analysis of the scheme,the result verifies that the mechanism can effectively improve the fault tolerance of the consensus mechanism,reduce the time of consensus to guarantee the security of the system.展开更多
Cooperative spectrum sensing in cog- nitive radio is investigated to improve the det- ection performance of Primary User （PU）. Meanwhile, cluster-based hierarchical coop- eration is introduced for reducing the overh...Cooperative spectrum sensing in cog- nitive radio is investigated to improve the det- ection performance of Primary User （PU）. Meanwhile, cluster-based hierarchical coop- eration is introduced for reducing the overhead as well as maintaining a certain level of sens- ing performance. However, in existing hierar- chically cooperative spectrum sensing algo- rithms, the robustness problem of the system is seldom considered. In this paper, we pro- pose a reputation-based hierarchically coop- erative spectrum sensing scheme in Cognitive Radio Networks （CRNs）. Before spectrum sensing, clusters are grouped based on the location correlation coefficients of Secondary Users （SUs）. In the proposed scheme, there are two levels of cooperation, the first one is performed within a cluster and the second one is carried out among clusters. With the reputa- tion mechanism and modified MAJORITY rule in the second level cooperation, the pro- posed scheme can not only relieve the influ- ence of the shadowing, but also eliminate the impact of the PU emulation attack on a rela- tively large scale. Simulation results show that, in the scenarios with deep-shadowing or mul- tiple attacked SUs, our proposed scheme ach- ieves a better tradeoff between the system robustness and the energy saving compared with those conventionally cooperative sensing schemes.展开更多
In mega-constellation Communication Systems, efficient routing algorithms and data transmission technologies are employed to ensure fast and reliable data transfer. However, the limited computational resources of sate...In mega-constellation Communication Systems, efficient routing algorithms and data transmission technologies are employed to ensure fast and reliable data transfer. However, the limited computational resources of satellites necessitate the use of edge computing to enhance secure communication.While edge computing reduces the burden on cloud computing, it introduces security and reliability challenges in open satellite communication channels. To address these challenges, we propose a blockchain architecture specifically designed for edge computing in mega-constellation communication systems. This architecture narrows down the consensus scope of the blockchain to meet the requirements of edge computing while ensuring comprehensive log storage across the network. Additionally, we introduce a reputation management mechanism for nodes within the blockchain, evaluating their trustworthiness, workload, and efficiency. Nodes with higher reputation scores are selected to participate in tasks and are appropriately incentivized. Simulation results demonstrate that our approach achieves a task result reliability of 95% while improving computational speed.展开更多
文摘In order to identify plants and recipes used in the treatment of malaria in Bagira,an ethnobotanical study was conducted from December 2013 to February 2014,by interviewing 85 traditional healers(46.9±12.0 average age;range:19-79 years).The direct interview using a questionnaire was used to collect ethnobotanical information.A specimen of each plant was collected
文摘Purpose:For a set of 1,561 Open Access(OA)and non-OA journals in business and economics,this study evaluates the relationships between four citation metrics-five-year Impact Factor(5IF),CiteScore,Article Influence(AI)score,and SCImago Journal Rank(SJR)-and the journal ratings assigned by expert reviewers.We expect that the OA journals will have especially high citation impact relative to their perceived quality(reputation).Design/methodology/approach:Regression is used to estimate the ratings assigned by expert reviewers for the 2021 CABS(Chartered Association of Business Schools)journal assessment exercise.The independent variables are the four citation metrics,evaluated separately,and a dummy variable representing the OA/non-OA status of each journal.Findings:Regardless of the citation metric used,OA journals in business and economics have especially high citation impact relative to their perceived quality(reputation).That is,they have especially low perceived quality(reputation)relative to their citation impact.Research limitations:These results are specific to the CABS journal ratings and the four citation metrics.However,there is strong evidence that CABS is closely related to several other expert ratings,and that 5IF,CiteScore,AI,and SJR are representative of the other citation metrics that might have been chosen.Practical implications:There are at least two possible explanations for these results:(1)expert evaluators are biased against OA journals,and(2)OA journals have especially high citation impact due to their increased accessibility.Although this study does not allow us to determine which of these explanations are supported,the results suggest that authors should consider publishing in OA journals whenever overall readership and citation impact are more important than journal reputation within a particular field.Moreover,the OA coefficients provide a useful indicator of the extent to which anti-OA bias(or the citation advantage of OA journals)is diminishing over time.Originality/value:This is apparently the first study to investigate the impact of OA status on the relationships between expert journal ratings and journal citation metrics.
文摘In response to the challenges presented by the unreliable identity of the master node,high communication overhead,and limited network support size within the Practical Byzantine Fault-Tolerant(PBFT)algorithm for consortium chains,we propose an improved PBFT algorithm based on XGBoost grouping called XG-PBFT in this paper.XG-PBFT constructs a dataset by training important parameters that affect node performance,which are used as classification indexes for nodes.The XGBoost algorithm then is employed to train the dataset,and nodes joining the system will be grouped according to the trained grouping model.Among them,the nodes with higher parameter indexes will be assigned to the consensus group to participate in the consensus,and the rest of the nodes will be assigned to the general group to receive the consensus results.In order to reduce the resource waste of the system,XG-PBFT optimizes the consensus protocol for the problem of high complexity of PBFT communication.Finally,we evaluate the performance of XG-PBFT.The experimental results show that XG-PBFT can significantly improve the performance of throughput,consensus delay and communication complexity compared to the original PBFT algorithm,and the performance enhancement is significant compared to other algorithms in the case of a larger number of nodes.The results demonstrate that the XG-PBFT algorithm is more suitable for large-scale consortium chains.
基金supported by the National Natural Science Foundation of China(NSFC)under Grant 61931005.
文摘Blockchain-based user-centric access network(UCAN)fails in dynamic access point(AP)management,as it lacks an incentive mechanism to promote virtuous behavior.Furthermore,the low throughput of the blockchain has been a bottleneck to the widespread adoption of UCAN in 6G.In this paper,we propose Overlap Shard,a blockchain framework based on a novel reputation voting(RV)scheme,to dynamically manage the APs in UCAN.AP nodes in UCAN are distributed across multiple shards based on the RV scheme.That is,nodes with good reputation(virtuous behavior)are likely to be selected in the overlap shard.The RV mechanism ensures the security of UCAN because most APs adopt virtuous behaviors.Furthermore,to improve the efficiency of the Overlap Shard,we reduce cross-shard transactions by introducing core nodes.Specifically,a few nodes are overlapped in different shards,which can directly process the transactions in two shards instead of crossshard transactions.This greatly increases the speed of transactions between shards and thus the throughput of the overlap shard.The experiments show that the throughput of the overlap shard is about 2.5 times that of the non-sharded blockchain.
基金Scientific Research Project of Higher Education Institutions in Hebei Province in 2025“Research on Government Procurement-Driven Green Governance of Hebei’s Manufacturing Industry”(Project No.:QN2025662)Social Science Fund of Hebei Province in 2024“Research on Informal Environmental Regulation Promoting Green Development of Hebei’s Manufacturing Industry”(Project No.:HB24GL036)Hebei Provincial Social Science Development Research Project,“Study on the Constraints and Implementation Paths of the Transformation from Dual Control of Energy Consumption to Dual Control of Carbon Emissions in Hebei Province”(Project No.:HBSKFZ25QN199)。
文摘Taking China’s 2018 value-added tax(VAT)credit refund reform as an exogenous shock to improve VAT neutrality,we use a difference-in-differences approach to explore how the reform affected corporate social responsibility(CSR).We find that the reform motivated firms to improve CSR performance.The reform has a“resource”effect,increasing internal funds and reducing financing costs,thereby enhancing firms’ability to undertake CSR.The reform also has a“reputation”effect,stimulating firms’willingness to engage in CSR to improve their reputations.CSR following the reform increases firm values and reduces bankruptcy risk.Our study provides fresh insights into VAT neutrality theory and is a reference for tax reform in emerging economies.
基金supported by the Open Foundation of Henan Key Laboratory of Cyberspace Situation Awareness(No.HNTS2022020)the Science and Technology Research Program of Henan Province of China(232102210134,182102210130)Key Research Projects of Henan Provincial Universities(25B520005).
文摘With the development of vehicle networks and the construction of roadside units,Vehicular Ad Hoc Networks(VANETs)are increasingly promoting cooperative computing patterns among vehicles.Vehicular edge computing(VEC)offers an effective solution to mitigate resource constraints by enabling task offloading to edge cloud infrastructure,thereby reducing the computational burden on connected vehicles.However,this sharing-based and distributed computing paradigm necessitates ensuring the credibility and reliability of various computation nodes.Existing vehicular edge computing platforms have not adequately considered themisbehavior of vehicles.We propose a practical task offloading algorithm based on reputation assessment to address the task offloading problem in vehicular edge computing under an unreliable environment.This approach integrates deep reinforcement learning and reputation management to address task offloading challenges.Simulation experiments conducted using Veins demonstrate the feasibility and effectiveness of the proposed method.
文摘Aim To study the implicit restriction mechanism for hidden action in multi stage dynamic game. Methods A reputation model for restriction on repeated principal agent relationship was established by using the theory on principal agent problem in information economics and the method of game theory to study the implicit restriction mechanism for hidden action. Results and Conclusion It is proved that there exists implicit restriction mechanism for the multi stage principal agent relationship, some conditions for effective restriction are derived, the design methods of implicit restriction mechanism are presented.
文摘Is He Living or Is He Dead is mainly about an outstanding painter Francois Millet who pretend to be dead in order to get reputation and money,because at that time a great artist has never been acknowledged until after he was starved and dead. Based on the critic approach of New Historicism, this thesis have analyzed how Millet subvert power and be contained by power, the capitalism and market, which criticized the phenomenon that the value of art is not decided by itself, but by power. No matter it is good or bad, if it is denied by power, it is valueless.
文摘Bitcoin has a bad reputation.The decentralised digital cryptocurrency,powered by a vast computer network,is notorious for the wild fluctuations in its value,the zeal of its supporters and its degenerate uses,such as extortion,buying drugs and hiring hitmen in the online bazaars of the'dark net'.比特币有一个坏名声。这种由一个庞大的计算机网络来驱动的去中心化数字加密货币,其恶名源于币值的剧烈波动、支持者的狂热追捧以及各种堕落的用途,如敲诈勒索、购买毒品和在'暗网'的在线市场雇佣杀手等。
基金supported by the National Natural Science Foundation of China (Nos. 61903056 and 61702066)the Chongqing Research Program of Basic Research and Frontier Technology (No. cstc2019jcyj-msxmX0681).
文摘As an emerging distributed technology, blockchain has begun to penetrate into many fields such as finance, healthcare, supply chain, intelligent transportation. However, the interoperability and value exchange between different independent blockchain systems is restricting the expansion of blockchain. In this paper, a notary group-based cross-chain interaction model is proposed to achieve the interoperability between different blockchains. Firstly, a notary election mechanism is proposed to choose one notary from the notary group to act as a bridge for cross-chain transactions. Secondly, a margin pool is introduced to limit the misconduct of the elected notary and ensure the value transfer between the involved blockchains. Moreover, a reputation based incentive mechanism is used to encourage members of the notary group to participate in cross-chain transactions. Ethereum-based experiments demonstrate that the proposed mechanism can provide an acceptable performance for cross-chain transactions and provide a higher security level than ordinary cross-chain mechanisms.
文摘MANET routing is critical and routing decision should be made sooner before the node leaves the network.Fast decisions always compensate network performance.In addition,most MANET routing protocols assume a friendly and cooperative environment,and hence are vulnerable to various attacks.Trust and Reputation would serve as a major solution to these problems.Learning the network characteristics and choosing right routing decisions at right times would be a significant solution.In this work,we have done an extensive survey of fault tolerant protocols and ant colony algorithms applied to routing in MANETs.We propose a QoS constrained fault tolerant ant lookahead routing algorithm which attempts to identify valid route and look-ahead route pairs which might help in choosing the alternate path in case of valid route failure.The results prove that the proposed algorithm takes better routing decisions with 20-30 percent improvement compared with existing ant colony algorithms.
基金supported in part by National Natural Science Foundation of China (NSFC) under Grant U1509219 and 2017YFB0802900
文摘A Service Level Agreement(SLA) is a legal contract between any two parties to ensure an adequate Quality of Service(Qo S). Most research on SLAs has concentrated on protecting the user data through encryption. However, these methods can not supervise a cloud service provider(CSP) directly. In order to address this problem, we propose a privacy-based SLA violation detection model for cloud computing based on Markov decision process theory. This model can recognize and regulate CSP's actions based on specific requirements of various users. Additionally, the model could make effective evaluation to the credibility of CSP, and can monitor events that user privacy is violated. Experiments and analysis indicate that the violation detection model can achieve good results in both the algorithm's convergence and prediction effect.
基金supported by the Program for Changjiang Scholars and Innovative Research Team in University under Grant No.IRT1078the Key Program of NSFC-Guangdong Union Foundation under Grant No.U1135002+1 种基金Major National S&T Program under Grant No.2011ZX03005-002the Fundamental Research Funds for the Central Universities under Grant No.JY10000903001
文摘Wireless Mesh Networks （WMNs） are vulnerable to various security threats because of their special infrastructure and communication mode, wherein insider attacks are the most challenging issue. To address this problem and protect innocent users from malicious attacks, it is important to encourage cooperation and deter malicious behaviors. Reputation systems constitute a major category of techniques used for managing trust in distributed networks, and they are effective in characterizing and quantifying a node＇s behavior for WMNs. However, conventional layered reputation mechanisms ignore several key factors of reputation in other layers; therefore, they cannot provide optimal performance and accurate malicious node identification and isolation for WMNs. In this paper, we propose a novel dynamic reputation mechanism, SLCRM, which couples reputation systems with a cross-layer design and node-security-rating classification techniques to dynamically detect and restrict insider attacks. Simulation results show that in terms of network throughput, packet delivery ratio, malicious nodes＇ identification, and success rates, SI_CRM imple- ments security protection against insider attacks in a more dynamic, effective, and efficient manner than the subjective logic and uncertainty-based reputation model and the familiarity-based reputation model.
文摘Volunteered geographic information(VGI)has entered a phase where there are both a substantial amount of crowdsourced information available and a big interest in using it by organizations.But the issue of deciding the quality of VGI without resorting to a comparison with authoritative data remains an open challenge.This article first formulates the problem of quality assessment of VGI data.Then presents a model to measure trustworthiness of information and reputation of contributors by analyzing geometric,qualitative,and semantic aspects of edits over time.An implementation of the model is running on a small data-set for a preliminary empirical validation.The results indicate that the computed trustworthiness provides a valid approximation of VGI quality.
基金supported by National Natural Science Foundation of China(Nos.71131002,71071045,71231004 and 71201042)
文摘In the last few years, cloud computing as a new computing paradigm has gone through significant development, but it is also facing many problems. One of them is the cloud service selection problem. As increasingly boosting cloud services are offered through the internet and some of them may be not reliable or even malicious, how to select trustworthy cloud services for cloud users is a big challenge. In this paper, we propose a multi-dimensional trust-aware cloud service selection mechanism based on evidential reasoning(ER) approach that integrates both perception-based trust value and reputation based trust value, which are derived from direct and indirect trust evidence respectively, to identify trustworthy services. Here, multi-dimensional trust evidence, which reflects the trustworthiness of cloud services from different aspects, is elicited in the form of historical users feedback ratings. Then, the ER approach is applied to aggregate the multi-dimensional trust ratings to obtain the real-time trust value and select the most trustworthy cloud service of certain type for the active users. Finally, the fresh feedback from the active users will update the trust evidence for other service users in the future.
文摘Users on the Internet usually require venues to provide better purchasing recommendations.This can be provided by a reputation system that processes ratings to provide recommendations.The rating aggregation process is a main part of reputation systems to produce global opinions about the product quality.Naive methods that are frequently used do not consider consumer profiles in their calculations and cannot discover unfair ratings and trends emerging in new ratings.Other sophisticated rating aggregation methods that use a weighted average technique focus on one or a few aspects of consumers′profile data.This paper proposes a new reputation system using machine learning to predict reliability of consumers from their profile.In particular,we construct a new consumer profile dataset by extracting a set of factors that have a great impact on consumer reliability,which serve as an input to machine learning algorithms.The predicted weight is then integrated with a weighted average method to compute product reputation score.The proposed model has been evaluated over three Movie Lens benchmarking datasets,using 10-folds cross validation.Furthermore,the performance of the proposed model has been compared to previous published rating aggregation models.The obtained results were promising which suggest that the proposed approach could be a potential solution for reputation systems.The results of the comparison demonstrated the accuracy of our models.Finally,the proposed approach can be integrated with online recommendation systems to provide better purchasing recommendations and facilitate user experience on online shopping markets.
基金partially supported by the University of Catania,Piano per la Ricerca 2016-2018-Linea di intervento 1(Chance),prot.2019-UNCTCLE-0343614the Italian MIUR,PRIN 2017 Project“Fluidware”(CUP H24I17000070001)。
文摘The purpose of the next internet of things(Io T)is that of making available myriad of services to people by high sensing intelligent devices capable of reasoning and real time acting.The convergence of Io T and multi-agent systems(MAS)provides the opportunity to benefit from the social attitude of agents in order to perform machine-to-machine(M2 M)cooperation among smart entities.However,the selection of reliable partners for cooperation represents a hard task in a mobile and federated context,especially because the trustworthiness of devices is largely unreferenced.The issues discussed above can be synthesized by recalling the well known concept of social resilience in Io T systems,i.e.,the capability of an Io T network to resist to possible attacks by malicious agent that potentially could infect large areas of the network,spamming unreliable information and/or assuming unfair behaviors.In this sense,social resilience is devoted to face malicious activities of software agents in their social interactions,and do not deal with the correct working of the sensors and other information devices.In this setting,the use of a reputation model can be a practicable and effective solution to form local communities of agents on the basis of their social capabilities.In this paper,we propose a framework for agents operating in an Io T environment,called Res Io T,where the formation of communities for collaborative purposes is performed on the basis of agent reputation.In order to validate our approach,we performed an experimental campaign by means of a simulated framework,which allowed us to verify that,by our approach,devices have not any economic convenience to performs misleading behaviors.Moreover,further experimental results have shown that our approach is able to detect the nature of the active agents in the systems(i.e.,honest and malicious),with an accuracy of not less than 11%compared to the best competitor tested and highlighting a high resilience with respect to some malicious activities.
基金This work is supported by the Key Research and Development Project of Sichuan Province(No.2021YFSY0012,No.2020YFG0307,No.2021YFG0332)the Key Research and Development Project of Chengdu(No.2019-YF05-02028-GX)+1 种基金the Innovation Team of Quantum Security Communication of Sichuan Province(No.17TD0009)the Academic and Technical Leaders Training Funding Support Projects of Sichuan Province(No.2016120080102643).
文摘In recent years,Blockchain is gaining prominence as a hot topic in academic research.However,the consensus mechanism of blockchain has been criticized in terms of energy consumption and performance.Although Proof-of-Authority(PoA)consensus mechanism,as a lightweight consensus mechanism,is more efficient than traditional Proof-of-Work(PoW)and Proof-of-Stake(PoS),it suffers from the problem of centralization.To this end,on account of analyzing the shortcomings of existing consensus mechanisms,this paper proposes a dynamic reputation-based consensus mechanism for blockchain.This scheme allows nodes with reputation value higher than a threshold apply to become a monitoring node,which can monitor the behavior of validators in case that validators with excessive power cause harm to the blockchain network.At the same time,the reputation evaluation algorithm is also introduced to select nodes with high reputation to become validators in the network,thus increasing the cost of malicious behavior.In each consensus cycle,validators and monitoring nodes are dynamically updated according to the reputation value.Through security analysis,it is demonstrated that the scheme can resist the attacks of malicious nodes in the blockchain network.By simulation experiments and analysis of the scheme,the result verifies that the mechanism can effectively improve the fault tolerance of the consensus mechanism,reduce the time of consensus to guarantee the security of the system.
基金ACKNOWLEDGEMENT This work was partially supported by the Na- tional Natural Science Foundation of China under Grant No. 61071127 and the Science and Technology Department of Zhejiang Pro- vince under Grants No. 2012C01036-1, No. 2011R10035.
文摘Cooperative spectrum sensing in cog- nitive radio is investigated to improve the det- ection performance of Primary User （PU）. Meanwhile, cluster-based hierarchical coop- eration is introduced for reducing the overhead as well as maintaining a certain level of sens- ing performance. However, in existing hierar- chically cooperative spectrum sensing algo- rithms, the robustness problem of the system is seldom considered. In this paper, we pro- pose a reputation-based hierarchically coop- erative spectrum sensing scheme in Cognitive Radio Networks （CRNs）. Before spectrum sensing, clusters are grouped based on the location correlation coefficients of Secondary Users （SUs）. In the proposed scheme, there are two levels of cooperation, the first one is performed within a cluster and the second one is carried out among clusters. With the reputa- tion mechanism and modified MAJORITY rule in the second level cooperation, the pro- posed scheme can not only relieve the influ- ence of the shadowing, but also eliminate the impact of the PU emulation attack on a rela- tively large scale. Simulation results show that, in the scenarios with deep-shadowing or mul- tiple attacked SUs, our proposed scheme ach- ieves a better tradeoff between the system robustness and the energy saving compared with those conventionally cooperative sensing schemes.
基金supported in part by the National Natural Science Foundation of China under Grant No.U2268204,62172061 and 61871422National Key R&D Program of China under Grant No.2020YFB1711800 and 2020YFB1707900+2 种基金the Science and Technology Project of Sichuan Province under Grant No.2023ZHCG0014,2023ZHCG0011,2022YFG0155,2022YFG0157,2021GFW019,2021YFG0152,2021YFG0025,2020YFG0322Central Universities of Southwest Minzu University under Grant No.ZYN2022032,2023NYXXS034the State Scholarship Fund of the China Scholarship Council under Grant No.202008510081。
文摘In mega-constellation Communication Systems, efficient routing algorithms and data transmission technologies are employed to ensure fast and reliable data transfer. However, the limited computational resources of satellites necessitate the use of edge computing to enhance secure communication.While edge computing reduces the burden on cloud computing, it introduces security and reliability challenges in open satellite communication channels. To address these challenges, we propose a blockchain architecture specifically designed for edge computing in mega-constellation communication systems. This architecture narrows down the consensus scope of the blockchain to meet the requirements of edge computing while ensuring comprehensive log storage across the network. Additionally, we introduce a reputation management mechanism for nodes within the blockchain, evaluating their trustworthiness, workload, and efficiency. Nodes with higher reputation scores are selected to participate in tasks and are appropriately incentivized. Simulation results demonstrate that our approach achieves a task result reliability of 95% while improving computational speed.
