DATA PRIVACY AND SECURITY PROTECTION STRATEGIES IN LIBRARY ELECTRONIC RESOURCES MANAGEMENT
DOI:
https://doi.org/10.62504/nexus742Keywords:
Data Privacy, Confidentiality, Ethical Considerations , Electronic Resources, CybersecurityAbstract
Security is a crucial aspect in the digital age, especially in the management and protection of information. As the volume of information processed increases, the need to organize knowledge and provide adequate security becomes more pressing. This research emphasizes the importance of cybersecurity in the context of digital libraries, which must comply with certain technological and regulatory standards to protect user data and guarantee privacy when accessing electronic resources. Libraries face various challenges in protecting personal data on their electronic resources. This research addresses topics such as user privacy, data encryption, access management, and compliance with privacy laws. By addressing these issues comprehensively, libraries can ensure the protection of user privacy while optimizing the benefits of digital resources in today's information environment. The October 2023 cyberattack by a hacker group known as Rhysida on the British Library's internet information system emphasizes the importance of cybersecurity and data privacy for digital libraries. This research aims to provide insights and solutions to address these challenges, ensuring digital libraries can operate securely and efficiently.
Downloads
References
Aksoy, C. (2024). Building a Cyber Security Culture for Resilient Organizations Against Cyber Attacks. In İşletme Ekonomi ve Yönetim Araştırmaları Dergisi (Vol. 7, Issue 1, pp. 96–110). Bayburt Universitesi. https://doi.org/10.33416/baybem.1374001
Aldaej, A. (2021). Notice of Retraction: Enhancing Cyber Security in Modern Internet of things (IoT) Using Intrusion Prevention Algorithm for IoT (IPAI). In IEEE Access (p. 1). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/ACCESS.2019.2893445
Aldhaheri, A., Alwahedi, F., Ferrag, M. A., & Battah, A. (2024). Deep learning for cyber threat detection in IoT networks: A review. In Internet of Things and Cyber-Physical Systems (Vol. 4, pp. 110–128). Elsevier BV. https://doi.org/10.1016/j.iotcps.2023.09.003
Alwahedi, F., Aldhaheri, A., Ferrag, M. A., Battah, A., & Tihanyi, N. (2024). Machine learning techniques for IoT security: Current research and future vision with generative AI and large language models. In Internet of Things and Cyber-Physical Systems (Vol. 4, pp. 167–185). Elsevier BV. https://doi.org/10.1016/j.iotcps.2023.12.003
Batool, H., Anjum, A., Khan, A., Izzo, S., Mazzocca, C., & Jeon, G. (2024). A secure and privacy preserved infrastructure for VANETs based on federated learning with local differential privacy. In Information Sciences (Vol. 652, p. 119717). Elsevier BV. https://doi.org/10.1016/j.ins.2023.119717
Bindra, S. S., & Aggarwal, A. (2024). Security in cyber physical systems: Transformation and challenges. In Journal of Autonomous Intelligence (Vol. 7, Issue 4). Frontier Scientific Publishing Pte Ltd. https://doi.org/10.32629/jai.v7i4.1336
Brighente, A., Conti, M., Renzone, G. Di, Peruzzi, G., & Pozzebon, A. (2024). Security and Privacy of Smart Waste Management Systems: A Cyber-Physical System Perspective. In IEEE Internet of Things Journal (Vol. 11, Issue 5, pp. 7309–7324). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/JIOT.2023.3322532
Chen, H., & Babar, M. A. (2024). Security for Machine Learning-based Software Systems: A Survey of Threats, Practices, and Challenges. In ACM Computing Surveys (Vol. 56, Issue 6, pp. 1–38). Association for Computing Machinery (ACM). https://doi.org/10.1145/3638531
Chen, T., Zeng, H., Lv, M., & Zhu, T. (2024). CTIMD: Cyber threat intelligence enhanced malware detection using API call sequences with parameters. In Computers and Security (Vol. 136, p. 103518). Elsevier BV. https://doi.org/10.1016/j.cose.2023.103518
Davies, J. (2023). Enhanced scalability and privacy for blockchain data using Merklized transactions. In Frontiers in Blockchain (Vol. 6). Frontiers Media SA. https://doi.org/10.3389/fbloc.2023.1222614
Demirer, M., Jiménez Hernández, D., Li, D., & Peng, S. (2024). Data, Privacy Laws and Firm Production: Evidence from the GDPR. In SSRN Electronic Journal. Elsevier BV. https://doi.org/10.2139/ssrn.4718871
Dong, C., Weng, J., Li, M., Liu, J. N., Liu, Z., Cheng, Y., & Yu, S. (2024). Privacy-Preserving and Byzantine-Robust Federated Learning. In IEEE Transactions on Dependable and Secure Computing (Vol. 21, Issue 2, pp. 889–904). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/TDSC.2023.3264697
Filani, J. (2024). Data Privacy in the Digital Age: Analyzing the impact of Technology of U.S Privacy Regulations. In SSRN Electronic Journal. Elsevier BV. https://doi.org/10.2139/ssrn.4762809
Hashem, T. N. (2024). Examining marketing cyber-security in the digital age: Evidence from marketing platforms. In International Journal of Data and Network Science (Vol. 8, Issue 2, pp. 1141–1150). Growing Science. https://doi.org/10.5267/j.ijdns.2023.11.020
Khan, I. A., Razzak, I., Pi, D., Khan, N., Hussain, Y., Li, B., & Kousar, T. (2024). Fed-Inforce-Fusion: A federated reinforcement-based fusion model for security and privacy protection of IoMT networks against cyber-attacks. In Information Fusion (Vol. 101, p. 102002). Elsevier BV. https://doi.org/10.1016/j.inffus.2023.102002
Kumari, S., Tulshyan, V., & Tewari, H. (2024). Cyber Security on the Edge: Efficient Enabling of Machine Learning on IoT Devices. In Information (Switzerland) (Vol. 15, Issue 3, p. 126). MDPI AG. https://doi.org/10.3390/info15030126
Kutschera, S., Slany, W., Ratschiller, P., Gursch, S., Deininger, P., & Dagenborg, H. (2024). Incidental Data: A Survey towards Awareness on Privacy-Compromising Data Incidentally Shared on Social Media. In Journal of Cybersecurity and Privacy (Vol. 4, Issue 1, pp. 105–125). MDPI AG. https://doi.org/10.3390/jcp4010006
M, V., & Murugan, R. (2024). The Role of Artificial Intelligence in Cyber Security. In International Journal of Innovative Research in Computer and Communication Engineering (Vol. 12, Issue 03, pp. 1635–1641). Ess & Ess Research Publications. https://doi.org/10.15680/ijircce.2024.1203044
Manalo, M. L. B., & Gallardo, R. D. (2024). Cyber Security Awareness and Educational Outcomes of Grade 4 Learners. In International Journal of Innovative Science and Research Technology (IJISRT) (pp. 1390–1422). International Journal of Innovative Science and Research Technology. https://doi.org/10.38124/ijisrt/ijisrt24apr1261
Masood, I., Daud, A., Wang, Y., Banjar, A., & Alharbey, R. (2024). A blockchain-based system for patient data privacy and security. In Multimedia Tools and Applications. Springer Science and Business Media LLC. https://doi.org/10.1007/s11042-023-17941-y
Munilla Garrido, G., Nair, V., & Song, D. (2024). SoK: Data Privacy in Virtual Reality. In Proceedings on Privacy Enhancing Technologies (Vol. 2024, Issue 1, pp. 21–40). Privacy Enhancing Technologies Symposium Advisory Board. https://doi.org/10.56553/popets-2024-0003
Noah, N., & Das, S. (2024). Privacy and Security in Extended Reality: Exploring the Risks of External Biometric Data Collection. In SSRN Electronic Journal. Elsevier BV. https://doi.org/10.2139/ssrn.4780358
Sangwan, U. (2024). Efficient Cyber Security Framework for IoT Using Machine Learning Algorithms. In Journal of Electrical Systems (Vol. 20, Issue 6, pp. 2444–2451). Science Research Society. https://doi.org/10.52783/jes.3233
Sendjaja, T., Irwandi, Prastiawan, E., Suryani, Y., & Fatmawati, E. (2024). Cybersecurity In The Digital Age: Developing Robust Strategies To Protect Against Evolving Global Digital Threats And Cyber Attacks. In International Journal of Science and Society (Vol. 6, Issue 1, pp. 1008–1019). Goacademica Research and Publishing. https://doi.org/10.54783/ijsoc.v6i1.1098
Sharma, S., & Nebhnani, M. (2024). Securing the Digital Frontier: Data Science Applications in Cyber security and Anomaly Detection. In International Journal of Food and Nutritional Sciences (Vol. 09, Issue 03). Institute for Advanced Studies. https://doi.org/10.48047/ijfans/09/03/33
Shen, X., Liu, Y., Li, F., & Li, C. (2024). Privacy-Preserving Federated Learning Against Label-Flipping Attacks on Non-IID Data. In IEEE Internet of Things Journal (Vol. 11, Issue 1, pp. 1241–1255). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/JIOT.2023.3288886
Singh, J., Reddy, A. M., Bande, V., Lakshmanarao, A., Rao, G. S., & Samunnisa, K. (2023). Enhancing Cloud Data Privacy with a Scalable Hybrid Approach: HE-DP-SMC. In Journal of Electrical Systems (Vol. 19, Issue 4, pp. 350–375). Science Research Society. https://doi.org/10.52783/jes.643
Subramani, J., Maria, A., Rajasekaran, A. S., & Lloret, J. (2024). Physically secure and privacy‐preserving blockchain enabled authentication scheme for internet of drones. In Security and Privacy (Vol. 7, Issue 3). Wiley. https://doi.org/10.1002/spy2.364
Sulaiman, M., Waseem, M., Ali, A. N., Laouini, G., & Alshammari, F. S. (2024). Defense Strategies for Epidemic Cyber Security Threats: Modeling and Analysis by Using a Machine Learning Approach. In IEEE Access (Vol. 12, pp. 4958–4984). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/ACCESS.2024.3349660
Szymanski, T. H. (2024). A Quantum-Safe Software-Defined Deterministic Internet of Things (IoT) with Hardware-Enforced Cyber-Security for Critical Infrastructures. In Information (Vol. 15, Issue 4, p. 173). MDPI AG. https://doi.org/10.3390/info15040173
Vargas, E. T., & Torres, E. (2024). Legal Challenges of Digital Copyright Laws in the Circulation of Digital Content. In Law and Economy (Vol. 3, Issue 1, pp. 1–10). Aurora Publishing House Limited. https://doi.org/10.56397/le.2024.01.01
Wa Nkongolo, M. (2024). Infusing Morabaraba game design to develop a cybersecurity awareness game (CyberMoraba). In International Conference on Cyber Warfare and Security (Vol. 19, Issue 1, pp. 240–250). Academic Conferences International Ltd. https://doi.org/10.34190/iccws.19.1.1957
Wang, W. (2024). Research on Data Security and Privacy Protection in the Context of Big Data. In Frontiers in Computing and Intelligent Systems (Vol. 7, Issue 1, pp. 29–33). Darcy & Roy Press Co. Ltd. https://doi.org/10.54097/astapa66
Wen, X., Chen, Y., Zhang, W., Jiang, Z. L., & Fang, J. (2024). Quantum protection scheme for privacy data based on trusted center. In Optics and Laser Technology (Vol. 169, p. 110130). Elsevier BV. https://doi.org/10.1016/j.optlastec.2023.110130
Wu, C. (2024). Data privacy: From transparency to fairness. In Technology in Society (Vol. 76, p. 102457). Elsevier BV. https://doi.org/10.1016/j.techsoc.2024.102457
Zheng, Y., Zhu, H., Lu, R., Guan, Y., Zhang, S., Wang, F., Shao, J., & Li, H. (2023). PHRkNN: Efficient and Privacy-Preserving Reverse kNN Query Over High-Dimensional Data in Cloud. In IEEE Transactions on Dependable and Secure Computing (pp. 1–15). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/TDSC.2023.3291715
Downloads
Published
Issue
Section
License
Copyright (c) 2024 Pratama Dahlian Persadha, Loso Judijanto, Melly Susanti, Heru Kreshna Reza (Author)
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
