A Context Approach to Improve the Data Anonymization Process

Abstract

Today, the protection of personal data is an important step in the development of an information system. This awakening of consciousness is happening as businesses grapple with growing volumes of data. No one wants to publicly expose their users’ data. The objective is not only to avoid sanctions but also bad media coverage and image damage when a company is the victim of a data breach. Personal and sensitive data should be confined to production environments and should not be copied to test environments, which poses a risk to its integrity. They should not be accessible in development and test databases to comply with GDPR (General Data Protection Regulation) regulations and to protect company data from potential breaches. Anonymization is a recommended technique for replacing personal data with non-identifying data for use in a test environment. This paper presents a socio-technical approach to data anonymization using the Contextual Graphs formalism which can help to easily represent user practices and gradually add them to an experience database. This can be used to improve the anonymization process in non-production environments.