Anonymization creates a challenge for evaluating the quality of the data since it prevents the identification and confirmation of errors, making it impossible to use another dataset to identify which values are correct.
Oct 12, 2022
Errors of Identifiers in Anonymous Databases: Impact on Data Quality. https://doi.org/10.1007/978-3-031-18050-7_53. Journal: Lecture Notes in Networks and ...
Aug 22, 2024 · Erosion of customer confidence: When data breaches occur due to re-identification, customers lose faith in an organisation's ability to protect ...
The experimental results of the study demonstrate that it is feasible to perform effective harmonization and anonymization on EHR data while preserving ...
Oct 1, 2016 · Data protection law protects only data relating to an identifiable individual, whereas “anonymous” data are free to be used by everybody. Usage ...
No useful database can ever be perfectly anonymous, and as the utility of data increases, the privacy decreases. Thus, easy, cheap, powerful reidentification ...
Jul 12, 2024 · This guide will help understand these processes, best practices, and their value in building confidence in and usefulness of your data.
In this study we argue that the traditional approach of evaluating the information quality of an anonymized (or otherwise modified) dataset is questionable.
ABSTRACT. Re-identification is a major privacy threat to public datasets containing individual records. Many privacy protection al-.
Statistical methods for anonymity, implying data perturbation and thereby loss of data quality, make appealing the methods proposed by computer scientists [20] ...