Blockchain-based Smart Contracts: A Systematic Mapping Study of Academic Research (2018)

Alharby, Maher; Aldweesh, Amjad; Moorsel, Aad van

doi:10.1109/iccbb.2018.8756390

Cited by 122 publications

(58 citation statements)

References 18 publications

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“…Furthermore, research in the smart contract technology has also evolved from the conceptual-based architecture to the application-oriented scenarios. According to the systematic mapping study conducted by Alharby et al (2018), 64% of the total 188 relevant papers they discovered on smart contracts were from the applications category compared to a very few application-oriented academic papers which they discovered in 2017. In 2017, they extracted only 24 papers on smart contracts in total, and their study shows that about 66% of the papers focused on the conceptual level identifying and tackling smart contract issues.…”

Section: Related Workmentioning

confidence: 99%

A Blockchain Platform for User Data Sharing Ensuring User Control and Incentives

2020

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We propose a new platform for user modeling with blockchains that allows users to share data without losing control and ownership of it and applied it to the domain of travel booking. Our new platform provides solution to three important problems: ensuring privacy and user control, and incentives for sharing. It tracks who shared what, with whom, when, by what means and for what purposes in a verifiable fashion. The paper presents a case study of applying the framework for a hotel reservation system as one of the enterprise nodes of Multichain which collects users' profile data and allows users to receive rewards while sharing their data with other travel service providers according to their privacy preferences expressed in smart contracts. The user data from the repository is converted into an open data format and shared via stream in the blockchain so that other nodes can efficiently process and use the data. The smart contract verifies and executes the agreed terms of use of the data and transfers digital tokens as a reward to the user. The smart contract imposes double deposit collateral to ensure that all participants act honestly. The paper also presents a performance evaluation of the new platform by analyzing latency and memory consumption with selected three test-scenarios and measuring the transaction cost for smart contracts deployment. The results show that the node responded quickly in all our cases with a befitting transaction cost.

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Section: Related Workmentioning

confidence: 99%

A Blockchain Platform for User Data Sharing Ensuring User Control and Incentives

2020

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“…A blockchain is a type of database that stores data in block units and links blocks to each other in chronological order [5,[10][11][12][13]. Each block depends on the previous block and all participants share a ledger.…”

Section: Blockchainmentioning

confidence: 99%

Automatic, location-privacy preserving dashcam video sharing using blockchain and deep learning

Kim

Jung

2020

Hum. Cent. Comput. Inf. Sci.

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A dashcam is a device that records events around a vehicle [1]. According to Embrain Trend Monitor research that surveys the satisfaction of dashcam users [2], the number of people who feel the need for a dashcam in their car has been steadily increasing. Because a dashcam records the event history of a vehicle, its videos can be used as evidence in disputes arising from accidents, both involving and observed by the dashcam owner. If a dashcam acquires video of accidents involving nearby vehicles, that video can be used as a record of the accident. In South Korea, public institutions often make announcements to look for witnesses of accidents and wait for a report. People share videos for various reasons [1], such as publicizing the truth, solving unfair cases, helping others, and benefitting the public. However, Kim et al. pointed out that waiting for a report and uploading a shared video via the web can reveal personal information such as location information or a fabricated Abstract Today, many people use dashcams, and videos recorded on dashcams are often used as evidence of accident fault. People can upload videos of dashcam recordings with specific accident clips and share the videos with others who request them, by providing the time or location of an accident. However, dashcam videos are erased when the dashcam memory is full, so periodic backup is necessary for video sharing. It is inconvenient for dashcam owners to search for and transmit a requested video clip from backup videos. In addition, anonymity is not ensured, which may reduce location privacy by exposing the video owner's location. To solve this problem, we propose a video sharing scheme with accident detection using deep learning coupled with automatic transfer to the cloud; we also propose ensuring data and operational integrity along with location privacy by using blockchain smart contracts. Furthermore, our proposed system uses proxy re-encryption to enhance the confidentiality of a shared video. Our experiments show that our proposed automatic video sharing system is cost-effective enough to be acceptable for deployment.

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“…In addition, some works partially related to our proposal have been published. Alharby et al [3], present a Systematic Mapping Study (SMS) of technology-oriented research in smart contracts. In this study, the authors followed the method presented by Petersen et al [52].…”

Section: A the Need For The Reviewmentioning

confidence: 99%

Model-Based Software Design and Testing in Blockchain Smart Contracts: A Systematic Literature Review

et al. 2020

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Blockchain technology promises to spark a real revolution. One of most important concepts associated with this technology is smart contracts, which enable the automatic execution of agreements and augur a world without intermediaries. The conditions and rules of "contracts" are established in a computer codes and trust is enforced by consensus among the participants. One relevant feature associated with smart contract is the immutability property, which establishes the non-alteration of blockchain network data after the clauses of the contract are been approved by all parties or entities involved. For this reason, smart contract development requires more effort and care than the development of other common programs. They require systematic mechanisms to collect requirements and functional specifications. In addition, it is necessary to verify and validate the agreed functionality and the implemented code before they are deployed in the blockchain platform. This paper presents a systematic literature review of primary studies in the field of Software Development Life Cycle, focusing on model-based software design and testing in the blockchain domain of smart contracts. This research aims to identify gaps and/or opportunities for further research. After carried out this review, it was observed that no clear methodology exists for evaluating and validating the quality either of this software or the overall development process. This means that software developers may implement smart contract code in which bugs and serious security vulnerabilities appear when the software is delivered to their customers.

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Blockchain-based Smart Contracts: A Systematic Mapping Study of Academic Research (2018)

Cited by 122 publications

References 18 publications

A Blockchain Platform for User Data Sharing Ensuring User Control and Incentives

A Blockchain Platform for User Data Sharing Ensuring User Control and Incentives

Automatic, location-privacy preserving dashcam video sharing using blockchain and deep learning

Model-Based Software Design and Testing in Blockchain Smart Contracts: A Systematic Literature Review

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