Background:The reputation system has been designed as an effective mechanism to reduce risks associated with online shopping for customers.However,it is vulnerable to rating fraud.Some raters may inject unfairly high ...Background:The reputation system has been designed as an effective mechanism to reduce risks associated with online shopping for customers.However,it is vulnerable to rating fraud.Some raters may inject unfairly high or low ratings to the system so as to promote their own products or demote their competitors.Method:This study explores the rating fraud by differentiating the subjective fraud from objective fraud.Then it discusses the effectiveness of blockchain technology in objective fraud and its limitation in subjective fraud,especially the rating fraud.Lastly,it systematically analyzes the robustness of blockchain-based reputation systems in each type of rating fraud.Results:The detection of fraudulent raters is not easy since they can behave strategically to camouflage themselves.We explore the potential strengths and limitations of blockchain-based reputation systems under two attack goals:ballot-stuffing and bad-mouthing,and various attack models including constant attack,camouflage attack,whitewashing attack and sybil attack.Blockchain-based reputation systems are more robust against bad-mouthing than ballot-stuffing fraud.Conclusions:Blockchain technology provides new opportunities for redesigning the reputation system.Blockchain systems are very effective in preventing objective information fraud,such as loan application fraud,where fraudulent information is fact-based.However,their effectiveness is limited in subjective information fraud,such as rating fraud,where the ground-truth is not easily validated.Blockchain systems are effective in preventing bad mouthing and whitewashing attack,but they are limited in detecting ballot-stuffing under sybil attack,constant attacks and camouflage attack.展开更多
Since the introduction of Bitcoin,numerous studies on Bitcoin mining attacks have been conducted,and as a result,many countermeasures to these attacks have been proposed.The reputation-based mining paradigm is a compr...Since the introduction of Bitcoin,numerous studies on Bitcoin mining attacks have been conducted,and as a result,many countermeasures to these attacks have been proposed.The reputation-based mining paradigm is a comprehensive countermeasure solution to this problem with the goal of regulating the mining process and preventing mining attacks.This is accomplished by incentivizing miners to avoid dishonest mining strategies using reward and punishment mechanisms.This model was validated solely based on game theoretical analyses,and the real-world implications of this model are not known due to the lack of empirical data.To shed light on this issue,we designed a simulated mining platform to examine the effectiveness of the reputation-based mining paradigm through data analysis.We implemented block withholding attacks in our simulation and ran the following three scenarios:Reputation mode,non-reputation mode,and no attack mode.By comparing the results from these three scenarios,interestingly,we found that the reputation-based mining paradigm decreases the number of block withholding attacks,and as a result,the actual revenue of individual miners becomes closer to their theoretical expected revenue.In addition,we observed that the confidence interval test can effectively detect block withholding attacks;however,the test also results in a small number of false positive cases.Since the effectiveness of the reputation-based model relies on attack detection,further research is needed to investigate the effect of this model on other dishonest mining strategies.展开更多
This perspective proposes that,by virtue of its sophisticated trust and consensus finding mechanisms,blockchain has the clear potential to substantially upgrade the processes and organization traditionally underpinnin...This perspective proposes that,by virtue of its sophisticated trust and consensus finding mechanisms,blockchain has the clear potential to substantially upgrade the processes and organization traditionally underpinning academic science and commercial technology development comprising funding,project delivery,generation of intellectual property,documentation and publication.For supporting this hypothesis,striking analogies between the concepts underlying blockchain technology with research are identified,and applied to the generation of verified knowledge in science and technology development.It is then elaborated how a blockchain-enabled token economy can efficiently and transparently incentivize and coordinate an integrative and community-inclusive participatory approach to fuel crowdsourcing of collective intelligence for contributing ideas,work,infrastructure,funding,data,validation,management,assessment,governance,arbitration and exploitation of projects.Quality,credibility and direction of projects are optimized by demanding collateral“skin-in-the-game”from contributors based on blockchain-enabled staking,reputation systems and prediction markets.This way research progress emerges as a chain of community generated and independently vetted blocks of scientific knowledge;these new blocks are concatenated with the state-of-the-art according to transparent consensus mechanisms.展开更多
文摘Background:The reputation system has been designed as an effective mechanism to reduce risks associated with online shopping for customers.However,it is vulnerable to rating fraud.Some raters may inject unfairly high or low ratings to the system so as to promote their own products or demote their competitors.Method:This study explores the rating fraud by differentiating the subjective fraud from objective fraud.Then it discusses the effectiveness of blockchain technology in objective fraud and its limitation in subjective fraud,especially the rating fraud.Lastly,it systematically analyzes the robustness of blockchain-based reputation systems in each type of rating fraud.Results:The detection of fraudulent raters is not easy since they can behave strategically to camouflage themselves.We explore the potential strengths and limitations of blockchain-based reputation systems under two attack goals:ballot-stuffing and bad-mouthing,and various attack models including constant attack,camouflage attack,whitewashing attack and sybil attack.Blockchain-based reputation systems are more robust against bad-mouthing than ballot-stuffing fraud.Conclusions:Blockchain technology provides new opportunities for redesigning the reputation system.Blockchain systems are very effective in preventing objective information fraud,such as loan application fraud,where fraudulent information is fact-based.However,their effectiveness is limited in subjective information fraud,such as rating fraud,where the ground-truth is not easily validated.Blockchain systems are effective in preventing bad mouthing and whitewashing attack,but they are limited in detecting ballot-stuffing under sybil attack,constant attacks and camouflage attack.
基金The research was sponsored by the Army Research Office and was accomplished under Grant Number W911NF-18-1-0483The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies,either expressed or implied,of the Army Research Office or the U.S.Government.The U.S.Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation herein.
文摘Since the introduction of Bitcoin,numerous studies on Bitcoin mining attacks have been conducted,and as a result,many countermeasures to these attacks have been proposed.The reputation-based mining paradigm is a comprehensive countermeasure solution to this problem with the goal of regulating the mining process and preventing mining attacks.This is accomplished by incentivizing miners to avoid dishonest mining strategies using reward and punishment mechanisms.This model was validated solely based on game theoretical analyses,and the real-world implications of this model are not known due to the lack of empirical data.To shed light on this issue,we designed a simulated mining platform to examine the effectiveness of the reputation-based mining paradigm through data analysis.We implemented block withholding attacks in our simulation and ran the following three scenarios:Reputation mode,non-reputation mode,and no attack mode.By comparing the results from these three scenarios,interestingly,we found that the reputation-based mining paradigm decreases the number of block withholding attacks,and as a result,the actual revenue of individual miners becomes closer to their theoretical expected revenue.In addition,we observed that the confidence interval test can effectively detect block withholding attacks;however,the test also results in a small number of false positive cases.Since the effectiveness of the reputation-based model relies on attack detection,further research is needed to investigate the effect of this model on other dishonest mining strategies.
文摘This perspective proposes that,by virtue of its sophisticated trust and consensus finding mechanisms,blockchain has the clear potential to substantially upgrade the processes and organization traditionally underpinning academic science and commercial technology development comprising funding,project delivery,generation of intellectual property,documentation and publication.For supporting this hypothesis,striking analogies between the concepts underlying blockchain technology with research are identified,and applied to the generation of verified knowledge in science and technology development.It is then elaborated how a blockchain-enabled token economy can efficiently and transparently incentivize and coordinate an integrative and community-inclusive participatory approach to fuel crowdsourcing of collective intelligence for contributing ideas,work,infrastructure,funding,data,validation,management,assessment,governance,arbitration and exploitation of projects.Quality,credibility and direction of projects are optimized by demanding collateral“skin-in-the-game”from contributors based on blockchain-enabled staking,reputation systems and prediction markets.This way research progress emerges as a chain of community generated and independently vetted blocks of scientific knowledge;these new blocks are concatenated with the state-of-the-art according to transparent consensus mechanisms.