Data privacy with heuristic anonymisation
by Sevgi Arca; Rattikorn Hewett
International Journal of Information and Computer Security (IJICS), Vol. 20, No. 1/2, 2023

Abstract: Abundance of data makes privacy more vulnerable than ever as it increases the attackers' ability to infer confidential data from multiple data sources. Anonymisation protects data privacy by ensuring that critical data are non-unique to any individual so that we can conceal the individual's identity. Existing techniques aim to minimally alter the original data so that either the anonymised data or its analytical results (e.g., classification) will not disclose certain privacy. Our research aims both. This paper presents HeuristicMin, an anonymisation approach that applies generalisations to satisfy user-specified anonymity requirements while maximising data retention (for analysis purposes). Unlike others, by exploiting monotonicity property of generalisation and simple heuristics for pruning, HeuristicMin provides an efficient exhaustive search for optimal generalised data. The paper articulates different meanings of optimality in anonymisation and compares HeuristicMin with well-known approaches analytically and empirically. HeuristicMin produces competitive results on the classification obtained from the anonymised data.

Online publication date: Wed, 04-Jan-2023

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Information and Computer Security (IJICS):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com