Peer Reviewed

Yes

Document Type

Conference Proceeding

Publication Date

2018

Abstract

In building a smart city, the public sector often sets various kinds of sensors or develops information systems to collect and analyze data to improve public service.Internet of Things (IoT) is utilized to improve the quality of citizen’s life in a city by enabling the collection and sharing of information related to transportation, public health, and environmental protection.However, the IoT data is stored and managed by a centralized cloud center, thus raising security and privacy concerns, which implies a single point of failure, easily being attacked, and performance bottleneck.The recent development of blockchain technology could be seen as an innovation that can offset the major drawbacks of IoT by changing the whole landscape of how data is stored, shared and managed securely.Blockchain technology allows for secure transactions of data by storing new information in different nodes and adding new information in its transaction history only when the nodes reach consensus.This distributed ledger system stores full transaction history which cannot be altered once a node approved by the trusted users in the blockchain network.As blockchain technology reduces the risk of manipulation, it has the potential for the handling of highly sensitive information such as land registry, voting records, educational certificates, and so on (Ølnes et al., 2017).This presents the new possibilities for e-government for storing, exchanging, and integrating data effectively and securely although blockchain technology still faces several challenges with software bugs, discrepancies and processing capabilities and other system vulnerability for its internal users (Al-Saquaf & Seidler, 2017; Atzori, 2015; Walport, 2016).Blockchain technology relies on ad-hoc processes in which relevant stakeholders come to a consensus on the technical code. Some researchers raised concerns about the potential role of blockchain technology in decentralizing the traditional form of institutional governance (Hsieh et al., 2018; MacDonald et al., 2016; Narayanan et al., 2016).While traditional governance mechanisms involve public, private, and civic organizations, digital governance requires the alignment of interests of internal users inside the governance network. Drawing on those various challenges of blockchain governance, we wanted to explore the ways in which blockchain can be used in the public sector and produce positive results.In particular, we decided to examine the potential benefits and challenges of peer-to-peer, decentralized networks in which different users (e.g., government agencies, research organizations, private firms) can join, verify, and share a constant stream of real-time data without much constraints (e.g., infrastructure, technology, personnel).Because the actual application of blockchain technology in the public sector is in its exploratory stage, this study intends to lay out some empirical foundations by simulating the environment in which practical benefits and challenges of blockchain governance can be examined and further discussed for future studies.For simulating a data governance environment backed by blockchain technology, we utilized an IoT network because it is increasingly recognized as an essential platform for capturing a continuous flow of data in building smart cities and working as a sensory system of a city.It is well known that security and privacy issues are major challenges to the IoT network and its data. In this paper, we examine how blockchain can complement or enhance data management in the IoT network environment.As we compare the theoretical concepts to the practical challenges arising from the simulated environment, our preliminary findings show that blockchain technology can enhance the data management process by mitigating some of the privacy and security concerns rising in the centralized IoT management.The organization of the rest of the paper is as follows. In section 2, we summarize the related work followed by our approach in section 3. Lastly, we discussed our preliminary findings in section 4.

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