Systems and methods for enhancing data protection by anonosizing structured and unstructured data and incorporating machine learning and artificial intelligence in classical and quantum computing environments

Abstract

Systems, computer-readable media, and methods for improving both data privacy/anonymity and data value, wherein real-world, synthetic, or other data related to a data subject can be used while minimizing re-identification risk by unauthorized parties and enabling data, including quasi-identifiers, related to the data subject to be disclosed to any authorized party by granting access only to the data relevant to that authorized party's purpose, time period, purpose, place and/or other criterion via the required obfuscation of specific data values, e.g., pursuant to the GDPR or HIPAA, by incorporating a given range of those values into a cohort, wherein only the defined cohort values are disclosed to the given authorized party. Privacy policies may include any privacy enhancement techniques (PET), including: data protection, dynamic de-identification, anonymity, pseudonymity, granularization, and/or obscurity policies. Such systems, media and methods may be implemented on both classical and quantum computing devices.