2019年10月24日，中共中央政治局就区块链技术发展现状和趋势进行了第18次集体学习。习近平总书记深刻分析了我国区块链技术发展现状，强调“把区块链作为核心技术自主创新的重要突破口”“加快推动区块链技术和产业创新发展”。总书记的讲话充分体现了党中央对区块链技术发展的前瞻判断。区块链从技术构想走入现实，日益凸显出赋能产业革新和助推经济建设的伟力，作为颠覆性的创新技术，其应用包括能源、金融、政府、教育等多种领域，以下前沿文献来自SCI中区块链应用于能源、汽车等领域的热点论文或高被引论文。
1.Blockchain technology in the energy sector: A systematic review of challenges and opportunities
能源领域的区块链技术：挑战与机遇的系统回顾
作者:Andoni, Merlinda; Robu, Valentin; Flynn, David;等.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS 卷: 100 页: 143-174 出版年: FEB 2019
Blockchains or distributed ledgers are an emerging technology that has drawn considerable interest from energy supply firms, startups, technology developers, financial institutions, national governments and the academic community. Numerous sources coming from these backgrounds identify blockchains as having the potential to bring significant benefits and innovation. Blockchains promise transparent, tamper-proof and secure systems that can enable novel business solutions, especially when combined with smart contracts. This work provides a comprehensive overview of fundamental principles that underpin blockchain technologies, such as system architectures and distributed consensus algorithms. Next, we focus on blockchain solutions for the energy industry and inform the state-of-the-art by thoroughly reviewing the literature and current business cases. To our knowledge, this is one of the first academic, peer-reviewed works to provide a systematic review of blockchain activities and initiatives in the energy sector. Our study reviews 140 blockchain research projects and startups from which we construct a map of the potential and relevance of blockchains for energy applications. These initiatives were systematically classified into different groups according to the field of activity, implementation platform and consensus strategy used. 1 Opportunities, potential challenges and limitations for a number of use cases are discussed, ranging from emerging peer-to-peer (P2P) energy trading and Internet of Things (IoT) applications, to decentralised marketplaces, electric vehicle charging and e-mobility. For each of these use cases, our contribution is twofold: first, in identifying the technical challenges that blockchain technology can solve for that application as well as its potential drawbacks, and second in briefly presenting the research and industrial projects and startups that are currently applying blockchain technology to that area. The paper ends with a discussion of challenges and market barriers the technology needs to overcome to get past the hype phase, prove its commercial viability and finally be adopted in the mainstream.
2.A Secure Charging Scheme for Electric Vehicles With Smart Communities in Energy Blockchain
能源区块链中智能社区电动汽车安全充电方案
作者:Su, Zhou; Wang, Yuntao; Xu, Qichao;等.
IEEE INTERNET OF THINGS JOURNAL 卷: 6 期: 3 页:4601-4613 出版年:JUN 2019
The smart community (SC), as an important part of the Internet of Energy (IoE), can facilitate integration of distributed renewable energy sources and electric vehicles (EVs) in the smart grid. However, due to the potential security and privacy issues caused by 'intrusted and opaque energy markets, it becomes a great challenge to optimally schedule the charging behaviors of EVs with distinct energy consumption preferences in SC. In this paper, we propose a contract-based energy blockchain for secure EV charging in SC. First, a permissioned energy blockchain system is introduced to implement secure charging services for EVs with the execution of smart contracts. Second, a reputation-based delegated Byzantine fault tolerance consensus algorithm is proposed to efficiently achieve the consensus in the permissioned blockchain. Third, based on the contract theory, the optimal contracts are analyzed and designed to satisfy EVs' individual needs for energy sources while maximizing the operator's utility. Furthermore, a novel energy allocation mechanism is proposed to allocate the limited renewable energy for EVs. Finally, extensive numerical results are carried out to evaluate and demonstrate the effectiveness and efficiency of the proposed scheme through comparison with other conventional schemes.
3.Blockchain-Based Decentralized Trust Management in Vehicular Networks
基于区块链的车辆网络分散式信任管理
作者:Yang, Zhe; Yang, Kan; Lei, Lei;等.
IEEE INTERNET OF THINGS JOURNAL 卷: 6期: 2页:1495-1505 出版年:APR 2019
Vehicular networks enable vehicles to generate and broadcast messages in order to improve traffic safety and efficiency. However, due to the nontrusted environments, it is difficult for vehicles to evaluate the credibilities of received messages. In this paper, we propose a decentralized trust management system in vehicular networks based on blockchain techniques. In this system, vehicles can validate the received messages from neighboring vehicles using Bayesian Inference Model. Based on the validation result, the vehicle will generate a rating for each message source vehicle. With the ratings uploaded from vehicles, roadside units (RSUs) calculate the trust value offsets of involved vehicles and pack these data into a "block." Then, each RSU will try to add their "blocks" to the trust blockchain which is maintained by all the RSUs. By employing the joint proof-of-work (PoW) and proof-of-stake consensus mechanism, the more total value of offsets (stake) is in the block, the easier RSU can find the nonce for the hash function (PoW). In this way, all RSUs collaboratively maintain an updated, reliable, and consistent trust blockchain. Simulation results reveal that the proposed system is effective and feasible in collecting, calculating, and storing trust values in vehicular networks.
4.Blockchain for Secure and Efficient Data Sharing in Vehicular Edge Computing and Networks
作者:Kang, Jiawen; Yu, Rong; Huang, Xumin;等.
车辆边缘计算和网络中安全高效数据共享的区块链
IEEE INTERNET OF THINGS JOURNAL 卷:6期:3页:4660-4670 出版年:JUN 2019
The drastically increasing volume and the growing trend on the types of data have brought in the possibility of realizing advanced applications such as enhanced driving safety, and have enriched existing vehicular services through data sharing among vehicles and data analysis. Due to limited resources with vehicles, vehicular edge computing and networks (VECONs) i.e., the integration of mobile edge computing and vehicular networks, can provide powerful computing and massive storage resources. However, road side units that primarily presume the role of vehicular edge computing servers cannot be fully trusted, which may lead to serious security and privacy challenges for such integrated platforms despite their promising potential and benefits. We exploit consortium blockchain and smart contract technologies to achieve secure data storage and sharing in vehicular edge networks. These technologies efficiently prevent data sharing without authorization. In addition, we propose a reputation-based data sharing scheme to ensure high-quality data sharing among vehicles. A three-weight subjective logic model is utilized for precisely managing reputation of the vehicles. Numerical results based on a real dataset show that our schemes achieve reasonable efficiency and high-level of security for data sharing in VECONs.
5.Blockchain for AI: Review and Open Research Challenges
区块链技术用于人工智能的开放研究挑战综述
作者:Salah, Khaled; Rehman, M. Habib Ur; Nizamuddin, Nishara;等.
IEEE ACCESS 卷: 7 页:10127-10149 出版年:2019
Recently, artificial intelligence (AI) and blockchain have become two of the most trending and disruptive technologies. Blockchain technology has the ability to automate payment in cryptocurrency and to provide access to a shared ledger of data, transactions, and logs in a decentralized, secure, and trusted manner. Also with smart contracts, blockchain has the ability to govern interactions among participants with no intermediary or a trusted third party. AI, on the other hand, offers intelligence and decision-making capabilities for machines similar to humans. In this paper, we present a detailed survey on blockchain applications for AI. We review the literature, tabulate, and summarize the emerging blockchain applications, platforms, and protocols specifically targeting AI area. We also identify and discuss open research challenges of utilizing blockchain technologies for AI.
