Developing a Blockchain-based Data Storage System Model to Improve Government Agencies’ Organizational Performance

Confidential documents in possession of government agencies are considered as assets that must be protected. Government agencies have started implementing cloud data storage systems to document data in a centralized network. However, this data storage system has been well-known as being threatened by data security, integrity, and data availability risks. On the other hand, blockchain technology, a decentralized, fast, secure, transparent, and recorded data storage system, is considered as the solution for mitigating these risks. Therefore, this study aims to identify the dominant risk factors of implementing the cloud computing storage system in government agencies potentially impacting its organizational performance and developing a risk-based data storage system that considers blockchain technology. This research used questionnaire surveys, case studies, and expert interviews to obtain its research objectives. The results demonstrated that six dominant risks included data theft and breaches, data corruption caused by virus attacks, limited storage space, data loss caused by system damage, data being accessed without particular access rights, and lack of guarantees from the system when a security threat occurred. A model for the blockchain-based cloud data storage system is proposed to address these risks and to improve the organizational performance of government agencies.

Blockchain; Cloud; Data storage system; Government agencies

To carry out its duties and functions mandated by law, government agencies require thorough data protection systems (Hill, 2014). Confidential documents and classified information in these agencies are considered as government assets that must be protected during use, storage, or transmission of information through the application of policies, education, and technology (Whitman and Mattord, 2018). Therefore, a secure data storage system in government agencies is needed, particularly for agencies that possess confidential data and information in their documents, considering the large volume and the high value of information that must be managed and protected from all possible threats.

Like many other countries, Indonesia has widely implemented cloud storage systems to document data and information in its government agencies. Cloud computing is a scalable and reliable platform that requires minimal management effort (Natesan and Chokkalingam, 2019; Wong et al., 2019). However, its security is still prone to cyber-attacks (Vurukonda and Rao, 2016). With the amount of data that keeps increasing every year, data integration and confidentiality have become crucial aspects that the institutions must consider in improving the data storage system (Irion, 2013; Lnenicka and Komarkova, 2019). In a traditional storage system, centralized data control does not guarantee the data's confidentiality, integrity, and authenticity. Therefore, a distributed data storage technology known for protecting data authenticity, confidentiality, and integrity is needed for government agencies (Rajalakshmi et al., 2018).

Digital technology has become one of the factors that influence the organizational performance of governmental agencies (Khin and Ho, 2019). The implementation of data and information storage systems influences the agency’s work performance in terms of having the security threat as a risk portfolio borne by the agency (Abd Al Ghaffar, 2020). Therefore, risk factors in the current data storage system and their potential impacts on the government agency’s organizational performance need to be examined. The risk-identifying process conducted in this paper was done through a risk management approach to identify the dominant risk factors.

Blockchain is a distributed ledger that uses public-key encryption and consensus protocol verifying the authenticity to record data on nodes called blocks in a secure, transparent, decentralized, cost-effective, and time-efficient manner (Cai, 2018). It can be perceived as a group of people sharing data using no intermediary agents, where trust between all the involved parties can still be built since all parties can see all the occurring transactions in the blockchain network (Berawi et al., 2020). Moreover, with its decentralized nature, the data is controlled by all participants in the network with a consensus protocol that rules the system (Rajalakshmi et al., 2018).

Previous studies (Ølnes et al., 2017; Alketbi et al., 2018; Razzaq et al., 2019) argued that blockchain has tremendous potential for government services, as it can help address issues such as human error, data privacy, security, and safety. Research regarding blockchain technology for cloud storage systems has been carried out extensively throughout the world (Tang et al., 2018; Deng et al., 2019; Sharma et al., 2020). However, implementing cloud storage systems adopting blockchain technology in the government sector is remains limited. Therefore, this study attempts to develop a model of the blockchain-based cloud storage system by identifying first the dominant risk factors from the implementation of the cloud storage system in the government agencies, which potentially impact their organizational performance, by taking into account a non-structural government agency in Indonesia as the case study. The findings of this study are expected to contribute insight for policymakers, practitioners, and researchers regarding the adoption of the blockchain mechanism in data storage systems to improve government agencies' organizational performance.

Cloud storage systems used in government agencies to store confidential documents are usually associated with data security, integrity, and availability. Therefore, this study attempted to identify the dominant risk factors in implementing the cloud storage system that affects the government agency’s organizational performance, in aiming to develop a framework for a cloud storage system mode that considers blockchain technology.

The development of the blockchain-based cloud storage system model was influenced by six dominant risk factors: theft and data breaches, data corruption caused by virus attacks, limited storage space, data loss caused by system damage, data being accessed without particular access rights, and lack of guarantees from the system when a security threat occurs. It can help improve the government agency’s organizational performance by providing a more efficient data delivery process. The proposed model only needs 4 days to complete a data compilation report in the case study agency compared to the conventional cloud storage system, which required 11 days. This study suggests future research is required to further develop the technical aspects of a blockchain-based storage system that can be implemented for all government agencies.

The authors would like to thank the Ministry of Research and Technology, Republic of Indonesia, for the support given to this research.

Abd Al Ghaffar, H.-A.N., 2020. Government Cloud Computing and National Security. Review of Economics and Political Science, pp. 2631–3561

Al Mudawi, N., Beloff, N., White, M., 2020. Issues and Challenges: Cloud Computing e-Government in Developing Countries. International Journal of Advanced Computer Science and Applications, Volume 11(4), pp. 7–11

Ali, K.E., Mazen, S.A., Hassanein, E.E., 2018. A Proposed Hybrid Model for Adopting Cloud Computing in e-Government. Future Computing and Informatics Journal, Volume 3(2), pp. 286–295

Alketbi, A., Nasir, Q., Talib, M.A., 2018. Blockchain for Government Services-Use Cases, Security Benefits and Challenges. In: 2018 15^th Learning and Technology Conference (L&T), pp. 112–119, Jeddah, Saudi Arabia

Berawi, M.A., Radjilun, M.K.Z., Sari, M., 2020. Developing Blockchain-Based Crowdfunding Model for Property Investment. In:  Second International Scientific Conference, SPBPU IDE 2020, St. Petersburg, Russia, October 22–23, 2020

Cai, C.W., 2018. Disruption of Financial Intermediation by FinTech: A Review on Crowdfunding and Blockchain. Accounting and Finance, Volume 58(4), pp. 965–992

Deng, Z., Ren, Y., Liu, Y., Yin, X., Shen, Z., Kim, H. J., 2019. Blockchain-Based Trusted Electronic Records Preservation in Cloud Storage. Computers, Materials and Continua, Volume 58(1), pp. 135–151

Feng, J., Chen, Y., 2013. A Fair Non-Repudiation Framework for Data Integrity in Cloud Storage Services. International Journal of Cloud Computing, Volume 2(1), pp. 20–43

Hatmoko, J.U.D., Astuti, P.K., Farania, S.N., 2021. Insuring Project Risks: Contractor Expectations versus Insurance Company Policies. International Journal of Technology, Volume 12(1), pp. 90–100

Hill, J.F., 2014. The Growth of Data Localization Post-Snowden: Analysis and Recommendations for U.S. Policymakers and Business Leaders. In: The Hague Institute for Global Justice, Conference on the Future of Cyber Governance

Hussain, S.A., Fatima, M., Saeed, A., Raza, I., Shahzad, R.K., 2017. Multilevel Classification of Security Concerns in Cloud Computing. Applied Computing and Informatics, Volume 13(1), pp. 57–65

Irion, K., 2013. Government Cloud Computing and National Data Sovereignty. Policy and Internet, Volume 4(3–4), pp. 40–71

Kanade, M., Mule, M., Shuaib, M., 2015. Improving Cloud Security using Data Partitioning and Encryption Technique. International Journal of Engineering Research and General Science, Volume 3(1), pp. 1245–1252

Khin, S., Ho, T.C.F., 2019. Digital Technology, Digital Capability and Organizational Performance: A Mediating Role of Digital Innovation. International Journal of Innovation Science, Volume 11(2), pp. 177–195

Ko, R.K.L., 2014. Data accountability in cloud systems. Security, privacy and trust in cloud systems. Edited by Surya Nepal and Mukaddim Pathan. Heidelberg, Germany, Springer

Lnenicka, M., Komarkova, J., 2019. Developing a Government Enterprise Architecture Framework to Support the Requirements of Big and Open Linked Data with the Use of Cloud Computing. International Journal of Information Management, Volume 46, pp. 124–141

Madyaningarum, N., Berawi, M.A., Miraj, P., 2018. Relationship between Leadership and Commitment with Quality Performance on U-Th-REE Processing Pilot Plant Construction in BATAN. Eksplorium, Volume 39(1), pp. 59–66

Moser, C.A., Kalton, G., 2017. Survey Methods in Social Investigation (Second). Aldershot: Dartmouth Publishing Company Ltd

Mukaka, M.M., 2012. A Guide to Appropriate Use of Correlation Coefficient in Medical Research. Malawi Medical Journal, Volume 24(3), pp. 69–71

Natesan, G., Chokkalingam, A., 2019. Optimal Task Scheduling in the Cloud Environment using a Mean Grey Wolf Optimization Algorithm. International Journal of Technology, Volume 10(1), pp. 126–136

Ølnes, S., Ubacht, J., Janssen, M., 2017. Blockchain in Government: Benefits and Implications of Distributed Ledger Technology for Information Sharing. Government Information Quarterly, Volume 34(3), pp. 355–364

PMBOK., 2017. A Guide to the Project Management Body of Knowledge (PMBOK Guide). Pennsylvania: Project Management Institute, Inc

Rajalakshmi, A., Lakshmy, K.V, Sindhu, M., Amritha, P.P., 2018. A Blockchain and IPFS Based Framework for Secure Research Record Keeping. International Journal of Pure and Applied Mathematics, Volume 119(15), pp. 1437–1442

Razzaq, A., Khan, M.M., Talib, R., Butt, A.D., Hanif, N., Afzal, S., Raouf, M.R., 2019. Use of Blockchain in Governance: A Systematic Literature Review. International Journal of Advanced Computer Science and Applications, Volume 10(5), pp. 685–691

Selvanathan, N., Poravi, G., 2018. Comparative Study on Decentralized Cloud Collaboration (DCC). In: The 3^rd International Conference for Convergence in Technology, Pune, India

Senthil, S., Kamalakannan, T., Shanthi, C., Radhakrishnan, D., 2019. Study on Cloud Storage and its Issues in Cloud Computing. International Journal of Management, Technology and Engineering, Volume 9(1), pp. 976–981

Sharma, P., Jindal, R., Borah, M.D., 2020. Blockchain Technology for Cloud Storage: A Systematic Literature Review. ACM Computing Surveys, Volume 53(4), pp. 1–32

Singh, I., Lee, S.W., 2018. Comparative Requirements Analysis for the Feasibility of Blockchain for Secure Cloud. Communications in Computer and Information Science, Volume 809, pp. 57–72

Tang, Y., Zou, Q., Chen, J., Li, K., Kamhoua, C.A., Kwiat, K., Njilla, L., 2018. ChainFS: Blockchain-Secured Cloud Storage. In: IEEE International Conference on Cloud Computing, CLOUD, 2018-July, CA, USA

Vurukonda, N., Rao, B.T., 2016. A Study on Data Storage Security Issues in Cloud Computing. Procedia Computer Science, Volume 92, pp. 128–135

Vyas, J., Modi, P., 2017. Providing Confidentiality and Integrity on Data Stored in Cloud Storage by Hash and Meta-data Approach. International Journal of Advance Research in Engineering, Volume 4(5), pp. 38–50

Whitman, M.E., Mattord, H.J., 2018. Principles of Information Security. Cengage Learning