Accenture Global Solutions Limited

Aishwarya Satish Padmanabhan

Emmanuel Munguia Tapia

Anshuma Chandak

In some examples, machine learning and rule-based identification, anonymization, and de-anonymization of sensitive structured and unstructured data may include receiving input data that is to be masked, and determining, for the input data, at least one type 'of entity extraction from a plurality of types of entity extractions to be performed on the input data. The at least one determined type of entity extraction may be performed on the input data, and at least one entity may be extracted from the input data. At least one replacement strategy may be determined from a plurality of replacement strategies for the at least one extracted entity. Further, the at least one determined replacement strategy may be applied to the at least one extracted entity to generate masked data.

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Santa Clara, CA, United States of America

Aishwarya Satish Padmanabhan