An Overview on Data Anonymization and Encryption in Data Mining

Exploring Privacy-Preserving Techniques in Data Mining

Abstract

Anonymization is a term explained in oxford dictionary as 'unknown'. Anonymization makes a protest indifferent from other items. It tends to be done by removing personally identifying information (PII) like Name, Social Security number, Phone number, Email, Address and so forth. De-identification is the way toward removing or obscuring any personally identifiable information from individual records in a way that minimizes the risk of unintended disclosure of the character of individuals and information about them. Anonymization of data alludes to the procedure of data de-identification that produces data where individual records can't be linked back to an original as they don't include the required translation variables to do as such. General data anonymization is a huge research region spanning numerous decades. In any case, the most generally utilized procedures for anonymization of data content are at present k-anonymity, L-Diversity and T-Closeness for privacy-preserving microdata discharge. In this paper we discuss about data anonymization and encryption in data mining.