Various anonymisation and pseudonymisation techniques exist, some of which are standardized. Nevertheless, the risk of a data breach for anonymised data and therefore that of re-identification of individuals remain significant. Therefore, institutions and commercial companies that may create or disseminate databases without identifiers are thus looking for a simple tool to measure this extreme risk of re-identification.
The shortcomings of current techniques associated with the regulations on personal data protection bring out a particular need: to propose a more practical method to measure the efficiency of the techniques implemented to protect anonymised personal data from the risk of re-identification. The Quantile at Risk (QaR) method provides an innovative solution to this quandary by providing a continuous assessment of the risk under consideration. It fills the gap between anonymised data and personal data, - including pseudonymised data - created by regulation on personal data conditioned primarily by compliancy.
The planned Workshop specifies a method to measure the quality of the anonymization of a data file, called QaR (Quantile at Risk) and how the QaR method results should be fine-tuned to data from different sectors (health care, banking, telecommunication, etc.). It is applicable to any database containing personal data and is intended to be used by all stakeholders processing personal data in any sector (e.g. healthcare, banking, telecommunication). It does not apply to databases containing among their inputs an individual identifier or transformed by hashing or other mathematical data transformation technics.
The secretariat of this Workshop is held by AFNOR and is proposed by QUANTOS
The kickoff meeting is scheduled for the 20th of April from 14:00 to 17:00. Should you need further information or should you wish to register to the kick-off meeting, please contact the Workshop Secretary Aylin KIP(aylin.kip@afnor.org)
Download the documents:
