Blockchain for Internet of Energy management: Review, solutions, and challenges

A smart contract is an agreement between two or more parties, which is executed by the computer code. The code does the execution without giving either party the ability to back out, so it ensures the trustless execution. The smart contract is one of the most important features in blockchain applications, which implements trusted transactions without third parties. However, with the rapid development, blockchain smart contracts have also exposed many security problems, and some attacks caused by contract vulnerabilities have led to terrible losses. In order to better deal with such dilemma, making a comprehensive survey about the security verification of blockchain smart contracts from major scientific databases is quite indispensable. Even though the significance of studying security verification of blockchain smart contracts is evident, it is really fresh yet. The major contributions of our survey work come from three aspects. First, after retrieving all-sided research studies, we select 53 most related papers to show the state-of-the art of this topic, where 20 papers focus on dealing with security assurance of blockchain smart contracts, and 33 papers focus on the correctness verification of blockchain smart contracts. Second, we propose a taxonomy toward the topic of security verification of blockchain smart contracts and discuss the pros and cons of each category of related studies. Third, through in-depth analysis of these studies, we come to know that the correctness verification of smart contracts based on the formal method has already become the more significant and more effective method to validate whether a smart contract is credible and accurate. So, we further present representative studies of formal verification of smart contracts in detail to demonstrate that using a formal method to validate blockchain smart contracts must have a promising and meritorious future.

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A Survey on Security Verification of Blockchain Smart Contracts

Applications of Blockchain (BC) technology and Cyber-Physical Systems (CPS) are increasing exponentially. However, framing resilient and correct smart contracts (SCs) for these smart application is a quite challenging task because of the complexity associated with them. SC is modernizing the traditional industrial, technical, and business processes. It is self-executable, self-verifiable, and embedded into the BC that eliminates the need for trusted third-party systems, which ultimately saves administration as well as service costs. It also improves system efficiency and reduces the associated security risks. However, SCs are well encouraging the new technological reforms in Industry 4.0, but still, various security and privacy challenges need to be addressed. In this paper, a survey on SC security vulnerabilities in the software code that can be easily hacked by a malicious user or may compromise the entire BC network is presented. As per the literature, the challenges related to SC security and privacy are not explored much by the authors around the world. From the existing proposals, it has been observed that designing a complex SCs cannot mitigate its privacy and security issues. So, this paper investigates various Artificial Intelligence (AI) techniques and tools for SC privacy protection. Then, open issues and challenges for AI-based SC are analyzed. Finally, a case study of retail marketing is presented, which uses AI and SC to preserve its security and privacy.

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Smart Contract Privacy Protection Using AI in Cyber-Physical Systems: Tools, Techniques and Challenges

Lithium-ion batteries are promising energy storage devices for electric vehicles and renewable energy systems. However, due to complex electrochemical processes, potential safety issues, and inherent poor durability of lithium-ion batteries, it is essential to monitor and manage batteries safely and efficiently. This study reviews the development of battery management systems during the past periods and introduces a multilayer design architecture for advanced battery management, which consists of three progressive layers. The foundation layer focuses on the system physical basis and theoretical principle, the algorithm layer aims at providing a comprehensive understanding of battery, and the application layer ensures a safe and efficient battery system through sufficient management. A comprehensive overview of each layer is presented from both academic and engineering perspectives. Future trends in research and development of next-generation battery management are discussed. Based on data and intelligence, the next-generation battery management will achieve better safety, performance, and interconnectivity.

Advanced battery management strategies for a sustainable energy future: Multilayer design concepts and research trends

Blockchain smart contracts formalization: Approaches and challenges to address vulnerabilities

Currently, Bitcoin and Ethereum are the two most popular cryptocurrency systems, especially Ethereum. It permits complex financial transactions or rules through scripts, which is called smart contracts. Since Ethereum smart contracts hold millions of dollars, their execution correctness is crucial against attacks which aim at stealing the assets. In this paper, we proposed a security assurance method for smart contract source code to find potential security risks. It contains two main functions, the first is syntax topological analysis of smart contract invocation relationship, to help developers to understand their code structure clearly; the second is logic risk (which may lead to vulnerabilities) detection and location, and label results on topology diagram. For developers' convenience, we have built a static analysis tool called SASC to generate topology diagram of invocation relationship and to find potential logic risks. We have made an evaluation on 2,952 smart contracts, experiment results proved that our method is intuitive and effective.

Security Assurance for Smart Contract

Battery swapping is a solution of electric vehicle (EV) battery refueling. For EV owners, the battery information and transaction’s correctness, openness, traceability and immutability is difficult to get guarantee in traditional centralized system. The trust lacking between EV owners and swapping station is caused, and becomes a big challenge to EV’s rapid development. An objective mechanism based on decentralized blockchain system is proposed to manage battery swapping and solve the trust lacking issue. With this solution, both battery’s life-cycle information and all operations histories are permanently saved in blockchain network. All key logics are driven by smart contracts, the battery price calculation and the digital currency exchange between EV owners and station are realized by smart contracts automatically and accurately. A primary prototype based on Ethereum is analyzed and implemented to illustrate the feasibility of managing battery swapping and refueling based on blockchain system to solve the trust lacking issue.

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Apply blockchain technology to electric vehicle battery refueling.

We propose a runtime composition method for creating various applications that comprise elaborate big data processing. Cloud platforms are required to be more capable at applying elaborate big data processing to various services for real businesses. Therefore, the platforms should be extensible to compound emerging runtimes. However, there are two major problems with this extensibility: providing an easy method for compounding a new runtime to the platforms and how to select the most efficient runtimes for each process in various situations. The runtime composition method is based on the model-driven engineering approach. The method searches the types of the most cost-efficient runtimes for each process under the requirements, creates the intermediate model, and, finally, generates files deployed to different processing engines. We designed and implemented four algorithms for selecting the runtimes. To confirm the ease of extending the method, we also designed and implemented four types of plugins. We found that we can separately append each type of information by installing these plugins. Experimental results show that variable depth search is the most preferable because of the accuracy of execution cost, but the greedy algorithm may be also preferable because of the balance among the execution time, the error rate, and the ease of implementation.

Runtime Composition for Extensible Big Data Processing Platforms

In these days, there are a lot of massive event data appeared every day because networked devices such as smartphones and kind of sensors become very common. Every service provider intends to analyze the event data and discovers a new business rule for real time event processing service. We proposed a methodology which integrates such kind of data analysis and service development using DFD (Data Flow Diagram) which is independent from implementations, and we developed its prototype for evaluations. The methodology and the tool separate the concern of a developer and an analyst, moreover, we succeeded to confirm that the prototype tool reduced actual analysis and service development costs dramatically.

Massive Event Data Analysis and Processing Service Development Environment Using DFD

This paper describes practices for multi-level modeling by only using existing modeling frameworks that comply Meta-Object Facility (MOF) We design modeling patterns for achieving the multi-level modeling methodologies on Eclipse Modeling Framework, and implement the dataflow model by applying the patterns Moreover, we attempt to compare the patterns regarding the facilitation of developing both our tool and plugins We found Orthogonal Classification Architecture (OCA) pattern is easier to develop our tool than powertypes pattern, but regarding plugins for our tool, powertypes pattern can define modelto-text transformation templates more simply than OCA pattern

Hidetoshi Kurihara

Papers

Security Assurance for Smart Contract

Apply blockchain technology to electric vehicle battery refueling.

Runtime Composition for Extensible Big Data Processing Platforms

Massive Event Data Analysis and Processing Service Development Environment Using DFD

Practical Multi-level Modeling on MOF-compliant Modeling Frameworks.