Towards an Ontology-Based Definition of Data Anonymization Policy for Cloud Computing and Big Data

The considerable increase in the use of cloud computing and big data solutions requires the use of advanced technologies to ensure data security, privacy and dependability. One of the possible solutions is the use of data anonymization techniques, which performs an important role in data privacy protection. There are several techniques and algorithms to implement data anonymization. However, specifications and guidelines to guide and standardize the use of these resources are needed. These guidelines, called anonymization policies, are considered an important asset in organizations that want to protect their customer personal data. Although the use of data anonymization brings great benefits, there are no clear directions for data anonymization policies, which ends up limiting its adoption by companies and organizations. This work presents a generic anonymization policy to be used in cloud and big data platforms. It also presents a draft ontology with explicit formal specifications for data anonymization policies. This ontology has three main intentions: (i) to standardize the use of data anonymization policies; (ii) share common understanding of the structure of data anonymization among people; (iii) enable reuse of data anonymization policies. In this work, an ongoing study case within the EUBra-BIGSEA project will be implemented.