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Boddy, A, Hurst, W, MacKay, M, El Rhalibi, A and Mwansa, M Data Analysis Techniques to Visualise Accesses to Patient Records in Healthcare Infrastructures. In: The Ninth International Conference on Cloud Computing, GRIDs, and Virtualization CLOUD COMPUTING 2018, 18 February 2018 - 22 February 2018, Barcelona. (Unpublished)
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CLOUD COMPUTING 2018 - Data Analysis Techniques to Visualise Accesses to Patient Records in Healthcare Infrastructures.pdf - Accepted Version Download (747kB) | Preview |
Abstract
Access to Electronic Patient Record (EPR) data is audited heavily within healthcare infrastructures. However, it is often left untouched in a data silo and only accessed on an ad hoc basis. Users with access to the EPR infrastructure are able to access the data of almost any patient without reprimand. Very Important Patients (VIPs) are an exception, for which the audit logs are regularly monitored. Otherwise, only if an official complaint is logged by a patient are audit logs reviewed. Data behaviour within healthcare infrastructures needs proactive monitoring for malicious, erratic or unusual activity. In addition, external threats, such as phishing or social engineering techniques to acquire a clinician’s logon credentials, need to be identified. This paper presents research towards a system which uses data analysis and visualisation techniques deployed in a cloud setting. The system adds to the defence-in-depth of the healthcare infrastructures by understanding patterns of data for profiling users’ behaviour to enable the detection and visualisation of anomalous activities. The results demonstrate the potential of visualising accesses to patient records for the situational awareness of patient privacy officers within healthcare infrastructures.
| Item Type: | Conference or Workshop Item (Paper) |
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| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Divisions: | Computer Science & Mathematics |
| Date Deposited: | 08 Feb 2019 11:38 |
| Last Modified: | 13 Apr 2022 15:16 |
| URI: | https://researchonline.ljmu.ac.uk/id/eprint/10040 |
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