Blockchain Papers

玉胜 谈

No abstract is available for this record.

HongQi Bi

In order to reduce the key update time delay of the Internet of Things and reduce the device location error rate and location time, a new key update and device location of Internet of Things based on smart contract was designed. Adopt improved MVIF security mechanism of both parties to build smart contract security mechanism, and the key update of the Internet of Things is realized through key predistribution, user registration and login, and key update. On this basis, multidimensional scaling technology is used to abstract Internet of Things devices into relative coordinates in multidimensional space, and the absolute coordinates are obtained by eliminating the distance estimation error to achieve Internet of Things device positioning. Experimental results show that the proposed method has a lower key update time delay, a lower amount of data used in the key update process, a lower positioning error rate of Internet of Things devices, and a shorter positioning time, which fully verifies the effectiveness of the proposed method.

Jian‐Zhang Chen, Haibo Tian, Fangguo Zhang

No abstract is available for this record.

Zexin Wang, Biwei Yan, Anming Dong

In the machine learning, data sharing between different participants can increase the amount of data, improve the quality of the dataset, and thereby improve the quality of the model. Under the condition of data supervision, federated learning, as a distributed machine learning, aims to protect data while training models through collaboration among all parties to achieve data sharing and improve model quality. However, there are still some issues. For instance, the lack of trust between the participants makes it impossible to establish a secure and reliable sharing mechanism. In addition, how to fairly share the benefits generated by the model, identify honest participants and punish malicious participants is still a challenge. In this paper, we propose a new federated learning scheme based on blockchain architecture for federated learning data sharing. Moreover, an incentive mechanism based on reputation points and Shaply values is proposed to improve the sustainability of the federated learning system, which provides a credible participation mechanism for data sharing based on federated learning and fair incentives. The experimental results and analysis show that the loss of federated learning is more smooth than that of centralized machine learning.

F. Panahov

With the development of electronic systems, ideas have repeatedly arisen to create an electronic analogue of cash for remote payment. Cryptocurrency technology was originally aimed at the absence of a trusted node - one whose actions are guaranteed to be true and who can confirm the correctness of other people's operations. For the first time, this problem was solved in the Bitcoin system due to the artificial complication of making changes to the transaction history register.

Adeeba Naaz, T. V. Pavan Kumar B, Maria Francis, Kotaro Kataoka

Authentication while maintaining anonymity when availing a service over the internet is a significant privacy challenge. Anonymous credentials (AC) address this by providing the user with a credential issued by a trusted entity that convinces the service provider (SP) that the user is authenticated but reveals no other information. The existing AC schemes assume a single trusted authority (certifier) that validates all the user attributes. In practice, however, a user may require different attributes to be attested by different certifiers. This means that the user has to get multiple credentials, increasing the burden on theSPwho has to verify each one of them. Moreover, complete anonymity can be misused. We propose adecentralized threshold revocable anonymous credential (DTRAC)scheme over blockchains that supports – a) attestation of attributes by multiple certifiers, and b) anonymity revocation through a set of distributed openers, by integrating threshold opening to the state-of-the-art threshold anonymous credential issuance scheme, Coconut [34]. DTRAC generates a single credential on attributes that are attested by multiple certifiers, freeing the SP from the hassle of verifying multiple credentials. We analyze the security of DTRAC formally in the universal composability (UC) framework. We also implement a prototype on Ethereum using smart contracts and give a detailed analysis of its performance.We compare the verification time for credentials with attributes attested by multiple certifiers in both DTRAC and Coconut and see that in terms of execution time and gas consumption, DTRAC performs significantly better than Coconut. It also scales better, with the performance gain of DTRAC over Coconut increasing linearly with the number of certifiers.

Yuan Yu, Li Yang, Wenjing Qin, Yasheng Zhou

No abstract is available for this record.

Xincheng Li, Xinchun Yin, Jianting Ning

Vehicular ad hoc network (VANET) is an emerging technology that can significantly improve the efficiency of transportation systems and mitigate traffic accidents by exchanging traffic-related messages or announcements. Nevertheless, there has not been a consensus on how to generate, distribute, and validate trustworthy announcements in such an untrusted wireless environment. Security and privacy, inspiration mechanism, and resource integration are significant challenges for announcement generation and dissemination. In this paper, a secure and trustworthy announcement dissemination scheme is realized for location-based service (LBS) application in VANET. A blockchain-assisted vehicular cloud (VC) architecture is proposed to harvest underutilized heterogeneous resources of vehicles participating in VANET. Moreover, the technologies of blockchain and smart contract are adopted to classify vehicles into different levels automatically by bidding for bonuses. What’s more, vehicles can generate trustworthy announcements with the help of neighbor vehicles by adopting the technology of threshold signature. Meanwhile, the reputation of announcements is evaluated for trust management. Formal security analysis shows that the proposed scheme satisfies fundamental security and privacy requirements in VANET. Experimental results show that the proposed scheme is robust and efficient.

Yipeng Zou, Tao Peng, Wentao Zhong, Kejian Guan · 5 authors

No abstract is available for this record.

Harsha Aggarwal, Rahul Johari, Deo Prakash Vidyarthi, Kalpana Gupta · 5 authors

No abstract is available for this record.

Omair Shafiq, Li Zhu, Xiantao Jiang, F. Richard Yu · 6 authors

The extensive use of vehicles nowadays and the emergency of autonomous driving urge the improvement of traffic safety. Prevalent approaches competent at preventing road accidents are inseparable from the trustworthy data acquisition. But in vehicular ad hoc networks (VANETs), data transmission and storage are unreliable due to constrained resource and unsteady topology. Currently, distribution is widely applied into VANETs for multifold data protection and blockchain becomes preferred with its distributed consensus and ledger for data trust protection. Therefore, we propose a system in this paper, which employs blockchain technology to secure the sharing of visual traffic information. As proposed, the sequence of frames is used for their integrity consensus, the transaction capacity is adjusted according to the frame types, and transcoding frames is defined via smart contracts; thus, traffic information gains more in-depth protection. With the proposed system, vehicles can confidently use the information for safety guidance.

Shaoyong Guo, Keqin Zhang, Bei Gong, Liandong Chen · 7 authors

As a new trusted data sharing pattern with privacy protection, the integration mechanism of blockchain and Federated Learning has attracted extensive attention. Generally, this mechanism uses blockchain technology to supervise the original data and calculation results, which ignores the supervision of the Federated Learning model and computing process. Therefore, we introduce the concepts of the sandbox and state channel to construct a new data privacy sharing paradigm via Blockchain and Federated Learning. Under this paradigm, we use state channel to connect Blockchain and Federated Learning. And state channel is used to create a “trusted sandbox” to instantiate Federated Learning tasks in the trustless edge computing environment. Meanwhile, we also mainly solve problems about data privacy sharing in Federated Learning and system performance degradation caused by data quality. The simulation results show that the proposed method has better performance and efficiency than the traditional data sharing method.

Xin Li

No abstract is available for this record.

Soumya Haridas, Shalu Saroj, Sairam Tushar Maddala, M. Kiruthika

No abstract is available for this record.

Puja Das, Moutushi Singh, Deepsubhra Guha Roy

No abstract is available for this record.

Sejin Han, Sooyong Park

As a service platform, blockchain has faced compliance issues since the General Data Protection Regulation (GDPR) came into effect in May 2018. Although many technical solutions have been proposed to solve the compatibility issues between blockchain and the GDPR, unresolved challenges remain. This study presents the gaps between the blockchain and the GDPR and explores solutions to bridge the gap.We review 91 previously published articles using a systematic literature review methodology. Then, we answer the following research questions: 1) Which solutions have been explored to allow the blockchain to comply with the GDPR? 2) What are the research gaps in the blockchain compliance field? Finally, we present five research gaps in this field: 1) development of a consent ontology model; 2) development of a methodology for monitoring fairness in the blockchain; 3) resolution of the contradiction between auditing and obfuscation; 4) development of a methodology for tracking controllers in the blockchain; and 5) integration of the different-purposed technical solutions without conflicts. Our research can raise the compatibility level of the blockchain and GDPR and guide the company adopting a blockchain to comply with the GDPR. Furthermore, it can advise the regulator to embrace new technologies into the GDPR while protecting a blockchain’s nature.

Chuxin Zhuang, Qingyun Dai, Yue Zhang

No abstract is available for this record.

Fidelia Cascini, Flavia Beccia, Francesco Andrea Causio, Andrea Gentili · 7 authors

The recent progress of genomics research is providing unprecedented insight into human genetic variance, susceptibility to disease and risk stratification. Current trends predict that a massive amount of genomic data will be produced in the upcoming years which, when coupled with the fast-paced development of the field, will create new social, ethical, and legal challenges. In the complex legislative environment of the European Union, genomic data sharing policies will have to weigh the benefits of scientific discovery against the ethical risks posed by the act of sharing sensitive data. In this complex, interconnected environment, blockchain provides a unique and novel solution to accountability, traceability, and transparency issues regarding genomic data sharing. Implementing a distributed ledger technology-based database could empower both patients and citizens to responsibly use genomic data pertaining to them because it allows for a higher degree of control over the recipients of their data and their uses. The blockchain technology will engage both data owners and policymakers to address the multiple issues of genomic data sharing and allow us to redefine the way we look at genomics.

Rabimba Karanjai, Lei Xu, Zhimin Gao, Lin Chen · 7 authors

No abstract is available for this record.

Minghao Li, Gansen Zhao, Ruilin Lai

No abstract is available for this record.

Srijanee Mookherji, Vanga Odelu, Rajendra Prasath

No abstract is available for this record.

Achref Haddaji, Samiha Ayed, Lamia Chaari Fourati

No abstract is available for this record.

Kashif Naseer Qureshi, Luqman Shahzad, Abdelzahir Abdelmaboud, Taiseer Abdalla Elfadil Eisa · 8 authors

The rapid advancement in the area of the Internet of Vehicles (IoV) has provided numerous\ncomforts to users due to its capability to support vehicles with wireless data communication. The\nexchange of information among vehicle nodes is critical due to the rapid and changing topologies,\nhigh mobility of nodes, and unpredictable network conditions. Finding a single trusted entity to\nstore and distribute messages among vehicle nodes is also a challenging task. IoV is exposed to\nvarious security and privacy threats such as hijacking and unauthorized location tracking of smart\nvehicles. Traceability is an increasingly important aspect of vehicular communication to detect and\npenalize malicious nodes. Moreover, achieving both privacy and traceability can also be a challenging\ntask. To address these challenges, this paper presents a blockchain-based efficient, secure, and\nanonymous conditional privacy-preserving and authentication mechanism for IoV networks. This\nsolution is based on blockchain to allow vehicle nodes with mechanisms to become anonymous and\ntake control of their data during the data communication and voting process. The proposed secure\nscheme provides conditional privacy to the users and the vehicles. To ensure anonymity, traceability,\nand unlinkability of data sharing among vehicles, we utilize Hyperledger Fabric to establish the\nblockchain. The proposed scheme fulfills the requirement to analyze different algorithms and\nschemes which are adopted for blockchain technology for a decentralized, secure, efficient, private,\nand traceable system. The proposed scheme examines and evaluates different consensus algorithms\nused in the blockchain and anonymization techniques to preserve privacy. This study also proposes\na reputation-based voting system for Hyperledger Fabric to ensure a secure and reliable leader\nselection process in its consensus algorithm. The proposed scheme is evaluated with the existing\nstate-of-the-art schemes and achieves better results.

Junaid Arshad, Muhammad Ajmal Azad, Alousseynou Prince, Jahid Ali · 5 authors

Reputation systems are an important means to facilitate trustworthy interactions between on-and off-chain services and users. However, contemporary reputation systems are typically dependent on a trusted central authority to preserve privacy of raters or on adding noise into the user feedback. Moreover, the accuracy of reputation values relies on the integrity of user feedback or input; this feedback should not be tampered with or misused for other purposes. This paper presents blockchain-based reputation system named REPUTABLE (A Decentralized Reputation System for blockchain-based Ecosystems), which computes the reputation of service providers and external services within a blockchain ecosystem through decentralized on-chain and off-chain implementation. Specifically, REPUTABLE not only ensures privacy, but also reliability, integrity and accuracy of reputation values, while incurring minimal overhead. It also enables performing certain data or statistical analytics functions on user feedback, whilst preserving security, privacy, accountability and unlinkability of participants and their feedback. We present a proof-of-concept implementation and a demonstration of the REPUTABLE system. Finally, by means of formal and empirical evaluation, we show the effectiveness of our proposed system to preserve the anonymity of user feedback and the high performance of its blockchain-based implementation.