Securing Public Health in The Digital Age: A Cybersecurity Case Study of Uk Local Council Health Services

Ugochukwu Anthony Igboko1* & Olofintuyi Adeolu Temitope2
1Digital and ICT Department, South Tyneside Council, United Kingdom
2Big Data Analytics, Sheffield Hallam University, United Kingdom
DOI –
http://doi.org/10.37502/IJSMR.2025.8503

Abstract

Introduction

While increasing the cyberattack surface and exposing sensitive patient data and vital service continuity to sophisticated threats, the fast digitisation of UK local council health services has improved care delivery. This study investigates institutional readiness and presents cybersecurity issues under decentralised public health governance.

Methodology

We conducted a qualitative systematic literature review, adhering to PRISMA guidelines. We used peer-reviewed articles and policy reports from 2019 to 2019–2025, sourced from Scopus and PubMed. Thematic analysis and critical evaluation methods (JBI checklist) were used to find common weaknesses, response actions to incidents, and how effective national cybersecurity efforts are at the local government level.

Design and Implementation

Drawing on synthesised insights, a novel cybersecurity framework was developed. We mapped the framework to identified management and technical challenge areas to facilitate practical implementation across diverse council IT environments.

Evaluation, Comparative Analysis and the strength of the framework.

We evaluated the efficacy of the framework through a hypothetical attack scenario at “WeCare Hospital”, which demonstrated improved containment and rapid recovery. A comparison with current solutions such as blockchain-based identity management and cloud privacy systems showed that it is better because it can be quickly set up, follows regulations well, and can grow easily, especially for on-site and mixed setups.

Conclusion

When the proposed framework is followed, it will significantly enhance cyber resilience for UK local council health services by integrating technical, organisational, and human factor measures. Its adoption promises to safeguard patient data, ensure regulatory compliance, and maintain service continuity.

Keywords: UK council, Healthcare, SLR, cyber resilience.

References

  • Al Kinoon, M. (2024). A Comprehensive and Comparative Examination of Healthcare Data Breaches: Assessing Security, Privacy, and Performance. Graduate Thesis and Dissertation 2023-2024. [online] Available at: https://stars.library.ucf.edu/etd2023/110/.
  • AlGhamdi, A.A., Niazi, M., Alshayeb, M. and Mahmood, S. (2024). Organizations’ readiness for insider attacks: A process‐oriented approach. Software Practice and Experience, 54(8), pp.1565–1589. doi:https://doi.org/10.1002/spe.3327.
  • Aslan, Ö., Aktuğ, S.S., Ozkan-Okay, M., Yilmaz, A.A. and Akin, E. (2023). A Comprehensive Review of Cyber Security Vulnerabilities, Threats, Attacks, and Solutions. Electronics, [online] 12(6), pp.1–42. doi:https://doi.org/10.3390/electronics12061333.
  • Beretas, C. (2024). Information Systems Security, Detection and Recovery from Cyber Attacks. Universal Library of Engineering Technology, [online] Volume 1(Issue 1). Available at: https://ulopenaccess.com/ulpages/fulltextUlete?PublishID=ULETE20240101_005.
  • Bose, B., Avasarala, B., Tirthapura, S., Chung, Y.-Y. and Steiner, D. (2017). Detecting Insider Threats Using RADISH: A System for Real-Time Anomaly Detection in Heterogeneous Data Streams. IEEE Systems Journal, 11(2), pp.471–482. doi:https://doi.org/10.1109/jsyst.2016.2558507.
  • Brett, M. (2022). Enabling cyber incident collaboration in UK local government thro…: Ingenta Connect. [online] Ingentaconnect.com. Available at: https://www.ingentaconnect.com/content/hsp/jcs/2022/00000005/00000003/art00006 [Accessed 22 Feb. 2025].
  • Butt, U.J. (2023). Developing a usable security approach for user awareness against ransomware. [online] bura.brunel.ac.uk. Available at: https://bura.brunel.ac.uk/handle/2438/26661.
  • Dasgupta, D., Akhtar, Z. and Sen, S. (2020). Machine learning in cybersecurity: a comprehensive survey. The Journal of Defense Modeling and Simulation: Applications, Methodology, Technology, 19(1), p.154851292095127. doi:https://doi.org/10.1177/1548512920951275.
  • Dib, M. and Pierre, S. (2023). Insider Attack Model Against HSM-Based Architecture. IEEE Access, 11, pp.86848–86858. doi:https://doi.org/10.1109/access.2023.3304994.
  • Elendu, C., Omeludike, E.K., Oloyede, P.O., Obidigbo, B.T. and Omeludike, J.C. (2024). Legal implications for clinicians in cybersecurity incidents: A review. Medicine, [online] 103(39), pp.e39887–e39887. doi:https://doi.org/10.1097/md.0000000000039887.
  • Hallows, R. (2020). Securitisation and the Role of the State in Delivering UK Cyber Security in a New-Medieval Cyberspace. [online] Available at: http://bear.buckingham.ac.uk/557/1/1502910%20Securitisation%20and%20the%20Role%20of%20the%20State%20in%20Delivering%20UK%20Cyber%20Security%20in%20a%20New-Medieval%20Cybersp.pdf.
  • Hossain, S.T., Yigitcanlar, T., Nguyen, K. and Xu, Y. (2023). Cybersecurity in Local Governments: A Review and Framework of Key Challenges. [online] doi:https://doi.org/10.2139/ssrn.4631885.
  • Hossain, S.T., Yigitcanlar, T., Nguyen, K. and Xu, Y. (2024). Local Government Cybersecurity Landscape: A Systematic Review and Conceptual Framework. Applied Sciences, [online] 14(13), p.5501. doi:https://doi.org/10.3390/app14135501.
  • Ibrahim, A., Thiruvady, D., Schneider, J. and Abdelrazek, M. (2020). The Challenges of Leveraging Threat Intelligence to Stop Data Breaches. [online] Semantic Scholar. doi:https://doi.org/10.3389/fcomp.2020.00036.
  • Khattabi, N. (2019). COULD SYSTEM-FOCUSED INCIDENT REVIEW IN HEALTHCARE BRIDGE THE GAP BETWEEN THE ‘WORK-AS- IMAGINED’ AND ‘THE WORK-AS- DONE’? [online] Available at: https://lup.lub.lu.se/student-papers/record/8994089/file/8994090.pdf [Accessed 9 Feb. 2025].
  • Lehto, M. (2022). Cyber-Attacks Against Critical Infrastructure. Computational Methods in Applied Sciences, 56, pp.3–42. doi:https://doi.org/10.1007/978-3-030-91293-2_1.
  • Maasberg, M., Warren, J. and Beebe, N.L. (2015). The Dark Side of the Insider: Detecting the Insider Threat through Examination of Dark Triad Personality Traits. 2015 48th Hawaii International Conference on System Sciences. doi:https://doi.org/10.1109/hicss.2015.423.
  • Mamidanna, S.K., Reddy, C.R.K. and Gujju, A. (2022). Detecting an Insider Threat and Analysis of XGBoost using Hyperparameter tuning. 2022 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI), pp.1–10. doi:https://doi.org/10.1109/accai53970.2022.9752509.
  • McCreight, R. (2023). Gauging the Impact of Satellite & Space Systems on Critical Infrastructure[CI]: Risk Management is Neither an Enigma nor a Mystery for CI Systems Security. Journal of Homeland Security and Emergency Management, 20(2), pp.183–208. doi:https://doi.org/10.1515/jhsem-2022-0054.
  • Michail, A. (2020). TACKLING THE CHALLENGES OF INFORMATION SECURITY INCIDENT REPORTING: A DECENTRALIZED APPROACH. [online] Available at: https://repository.uel.ac.uk/download/9c570940f180b4fe5201dd0579a05625d8784d0729bab6aeff1b7676ffd7ac32/5157004/2020_DProf_Michail.pdf.
  • Moore, G., Khurshid, Z., McDonnell, T., Rogers, L. and Healy, O. (2023). A resilient workforce: patient safety and the workforce response to a cyber-attack on the ICT systems of the national health service in Ireland. BMC Health Services Research, 23(1). doi:https://doi.org/10.1186/s12913-023-10076-8.
  • Mott, G., Nurse, J.R.C. and Baker-Beall, C. (2023). Preparing for future cyber crises: lessons from governance of the coronavirus pandemic. Policy Design and Practice, 6(2), pp.1–22. doi:https://doi.org/10.1080/25741292.2023.2205764.
  • Naik, N., Jenkins, P. and Savage, N. (2018). Threat-Aware Honeypot for Discovering and Predicting Fingerprinting Attacks Using Principal Components Analysis. 2018 IEEE Symposium Series on Computational Intelligence (SSCI), IEEE Xplore, pp.623–630. doi:https://doi.org/10.1109/SSCI.2018.8628658.
  • Patterson, C.M., Nurse, J.R.C. and Franqueira, V.N.L. (2024). ‘I don’t think we’re there yet’: The practices and challenges of organisational learning from cyber security incidents. Computers & Security, [online] 139(1), p.103699. doi:https://doi.org/10.1016/j.cose.2023.103699.
  • Priya, D.V.S., Sethuraman, S.C. and Khan, M.K. (2023). Container security: Precaution levels, mitigation strategies, and research perspectives. Computers & Security, [online] 135, p.103490. doi:https://doi.org/10.1016/j.cose.2023.103490.
  • Rajesh Kanna, P. and Santhi, P. (2024). Exploring the landscape of network security: a comparative analysis of attack detection strategies. Journal of ambient intelligence & humanized computing/Journal of ambient intelligence and humanized computing, pp.1–18. doi:https://doi.org/10.1007/s12652-024-04794-y.
  • Safitra, M.F., Lubis, M. and Fakhrurroja, H. (2023). Counterattacking Cyber Threats: A Framework for the Future of Cybersecurity. Sustainability, [online] 15(18), p.13369. doi:https://doi.org/10.3390/su151813369.
  • Shackelford, S. (2024). Wargames. Routledge eBooks, pp.127–152. doi:https://doi.org/10.4324/9781003344124-8.
  • Shalev, N., Keidar, I., Weinsberg, Y., Moatti, Y. and Ben-Yehuda, E. (2017). WatchIT: Who Watches Your IT Guy? Proceedings of the 26th Symposium on Operating Systems Principles, pp.515–530. doi:https://doi.org/10.1145/3132747.3132752.
  • Staves, A., Anderson, T., Balderstone, H., Green, B., Gouglidis, A. and Hutchison, D. (2022). A Cyber Incident Response and Recovery Framework to Support Operators of ICS and Critical National Infrastructure. International Journal of Critical Infrastructure Protection, 37, p.100505. doi:https://doi.org/10.1016/j.ijcip.2021.100505.
  • Tien, C., Huang, T., Tien, C., Huang, T. and Kuo, S. (2019). KubAnomaly: Anomaly detection for the Docker orchestration platform with neural network approaches. Engineering Reports, 1(5). doi:https://doi.org/10.1002/eng2.12080.
  • Valbø, T. (2023). Cloud adoption and cyber security in public organizations: an empirical investigation on Norwegian municipalities. Unit.no. [online] doi:no.uia:inspera:143804570:99658401.
  • Wang, Z.Q. and El Saddik, A. (2023). DTITD: An Intelligent Insider Threat Detection Framework Based on Digital Twin and Self-Attention Based Deep Learning Models. IEEE access, 11, pp.114013–114030. doi:https://doi.org/10.1109/access.2023.3324371.
  • Xiao, H., Zhu, Y., Zhang, B., Lu, Z., Du, D. and Liu, Y. (2024). Unveiling shadows: A comprehensive framework for insider threat detection based on statistical and sequential analysis. Computers & Security, 138, pp.103665–103665. doi:https://doi.org/10.1016/j.cose.2023.103665.
  • Xu, F., Hsu, C., Wang, T. and Paul Benjamin Lowry (2023). The antecedents of employees’ proactive information security behaviour: The perspective of proactive motivation. Information Systems Journal, 34(4), pp.1144–1174. doi:https://doi.org/10.1111/isj.12488.
  • Zacharis, A. and Patsakis, C. (2023). AiCEF: an AI-assisted cyber exercise content generation framework using named entity recognition. International Journal of Information Security, 22(5), pp.1333–1354. doi:https://doi.org/10.1007/s10207-023-00693-z