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ARTPHIL: reversible de-identification of free-text using an integrated model
conference contribution
posted on 2023-06-10, 01:54 authored by Bayan Alabdullah, Natalia BeloffNatalia Beloff, Martin WhiteMartin WhiteOrganisations that collect and maintain individual data face the challenge of preserving privacy and security when using, archiving, or sharing these data. De-identification tools are essential for minimising the privacy risk. However, current data de-identification and anonymisation methods are widely used to alter the original data in a way that cannot be recovered. This results in data distortion and, hence, the substantial loss of knowledge within the data. To address this issue, this paper introduces the concept of reversible data de-identification methods to de-identify unstructured health data under the Health Insurance Portability and Accountability Act (HIPAA) guidelines. The model integrates Philter [9], the state-of-the-art tool for extracting personal identifiers from free-text, to detect confidential information and encrypt them with E-ART, lightweight encryption algorithm E-ART [10]. The performance of the proposed model ARTPHIL is evaluated using i2b2 data corpus in terms of recall, precision, F-measure and execution time. The results of the experiment are consistent with the recent de-identification method with recall of 96.93%. More importantly, the original data can be recovered, if needed, and authenticated.
History
Publication status
- Published
File Version
- Accepted version
Journal
EAI SPNCE 2021 - 4th EAI International Conference on Security and Privacy in New Computing EnvironmentsISSN
1867-8211Publisher
SpringerExternal DOI
Volume
423Event name
EAI SPNCE 2021 - 4th EAI International Conference on Security and Privacy in New Computing EnvironmentsEvent location
Qinhuangdao, People’s Republic of China (Online)Event type
conferenceEvent date
December 10-11, 2021ISBN
9783030967901Series
Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications EngineeringDepartment affiliated with
- Informatics Publications
Full text available
- Yes
Peer reviewed?
- Yes
Legacy Posted Date
2021-12-01First Open Access (FOA) Date
2023-03-14First Compliant Deposit (FCD) Date
2021-11-30Usage metrics
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