Big data privacy anonymization algorithms: a review

This paper provides an overview of big data privacy challenges, variety and classification of privacy algorithms. Information of each individual wish that his private information is not revealed in some or the other way. Privacy preservation plays a vital role in preventing individual private data. Anonymization is a process of removing personally identifiable information from the data set. Under anonymization category k-anonymity, L-diversity and T-closeness algorithms is discussed in detail. The comparison of anonymization algorithms is carried out for eight parameters.