BLOCKCHAIN TECHNOLOGY AND INFORMATION SECURITY MANAGEMENT: A CASE OF NIGERIAN LIBRARIES
Keywords:
Blockchain, Information Security, Libraries, Nigeria, Data IntegrityAbstract
Information security is increasingly critical for libraries in Nigeria as they shift from traditional systems to digital cataloguing and cloud storage. However, these libraries face significant challenges, including unauthorized access to digital resources, inadequate data backup, lack of encryption, and insufficient staff awareness of cybersecurity practices. These vulnerabilities threaten the confidentiality, integrity, and availability of library information, compromising the reliability of knowledge repositories in both academic and public institutions. Blockchain technology offers a potential solution by providing a secure, decentralized framework that enhances information governance. Its features, immutability, distributed ledgers, and cryptographic validation can safeguard library data from tampering and unauthorized changes. By implementing smart contracts and blockchain-based access logs, libraries can ensure data authenticity and maintain secure borrowing systems. This paper employs a qualitative case study methodology, focusing on a university library in Nigeria. Through interviews with ICT personnel and library administrators, along with document reviews, the study identifies key security weaknesses, such as inadequate logging mechanisms and limited awareness of advanced technologies. The findings highlight the necessity for innovative information management approaches in Nigerian libraries. The study concludes that integrating blockchain, beginning with metadata protection and document authentication, could yield long-term benefits in digital archiving and user access control. Consequently, library managers and policymakers should prioritize investments in blockchain literacy, infrastructure, and pilot programs to enhance information security
References
Al Rawajbeh, M., Alzyadat, W., Kaabneh, K., Afaneh, S., Alrwashdeh, D. F., Albayaydah, H. S., & Alhadid, I. H. (2023). A new model for security analysis of network anomalies for IoT devices. International Journal of Data and Network Science, 7(3), 1241–1248. https://doi.org/10.5267/j.ijdns.2023.5.001
Aswir, & Misbah, H. (2018). Smartphones as personal digital archives? Recentering migrant authority as curating and storytelling subjects. Photosynthetica, 2(1), 1–13. http://link.springer.com/10.1007/978-3-319-76887-8
Beillahi, S. M., Ciocarlie, G., Emmi, M., & Enea, C. (2020). Behavioral simulation for smart contracts. Proceedings of the ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI), 20(4), 470–486. https://doi.org/10.1145/3385412.3386022
Catelli, R., Gargiulo, F., Damiano, E., Esposito, M., & De Pietro, G. (2021). Clinical de-identification using sub-document analysis and ELECTRA. Proceedings - 2021 IEEE International Conference on Digital Health, ICDH 2021, 266–275. https://doi.org/10.1109/ICDH52753.2021.00050
Gourisetti, S. N. G., Mylrea, M., & Patangia, H. (2020). Cybersecurity vulnerability mitigation framework through empirical paradigm: Enhanced prioritized gap analysis. Future Generation Computer Systems, 105, 410–431. https://doi.org/10.1016/j.future.2019.12.018
Hu, T., Liu, X., Chen, T., Zhang, X., & Huang, X. (2021). Transaction-based classification and detection approach for Ethereum smart contract. Information Processing and Management, 58(December 2020), 2–19.
Islam, U., Muhammad, A., Mansoor, R., Hossain, M. S., Ahmad, I., Eldin, E. T., Khan, J. A., Rehman, A. U., & Shafiq, M. (2022). Detection of Distributed Denial of Service (DDoS) Attacks in IOT Based Monitoring System of Banking Sector Using Machine Learning Models. Sustainability (Switzerland), 14(14). https://doi.org/10.3390/su14148374
Leka, E., Selimi, B., & Lamani, L. (2019). Systematic Literature Review of Blockchain Applications: Smart Contracts. 2019 International Conference on Information Technologies, InfoTech 2019 - Proceedings, December. https://doi.org/10.1109/InfoTech.2019.8860872
Li, J., Lyu, L., Liu, X., Zhang, X., & Lyu, X. (2022). FLEAM: A Federated Learning Empowered Architecture to Mitigate DDoS in Industrial IoT. IEEE Transactions on Industrial Informatics, 18(6), 4059–4068. https://doi.org/10.1109/TII.2021.3088938
Lohmann, P. A., Albuquerque, C., & Machado, R. (2023). Systematic Literature Review of Threat Modeling Concepts. International Conference on Information Systems Security and Privacy, March, 163–173. https://doi.org/10.5220/0011783000003405
Meneghello, F., Calore, M., Zucchetto, D., Polese, M., & Zanella, A. (2019). IoT: Internet of Threats? A Survey of Practical Security Vulnerabilities in Real IoT Devices. IEEE Internet of Things Journal, 6(5), 8182–8201. https://doi.org/10.1109/JIOT.2019.2935189
Shrivastava, S., & Johari, P. K. (2022). Convolutional Neural Network Approach for Mobile Banking Fraudulent Transaction to Detect Financial Frauds. International Journal of Engineering Technology and Management Sciences, 6(1), 30–37. https://doi.org/10.46647/ijetms.2022.v06i01.005
Steffen ETH Zurich Switzerland, S., Bichsel ETH Zurich Switzerland, B., Vechev ETH Zurich Switzerland, M., Steffen, S., Bichsel, B., & Vechev, M. (2022). Zapper: Smart Contracts with Data and Identity Privacy; Zapper: Smart Contracts with Data and Identity Privacy. https://doi.org/10.1145/3548606.3560622
Tsabary, I., Manuskin, A., & Eyal, I. (2022). LedgerHedger: Gas Reservation for Smart-Contract Security. In Cryptology ePrint Archive (Vol. 1, Issue 1). Association for Computing Machinery. https://eprint.iacr.org/2022/056
Williams, P., Kaylan, I., Daoud, H., & Bayoumi, M. (2022). Internet of Things A survey on security in internet of things with a focus on the impact of emerging technologies. Internet of Things, 19(7), 10–23. https://doi.org/10.1016/j.iot.2022.100564
