{'fraction_non_alphanumeric': 0.011185682326621925, 'fraction_numerical': 0.0, 'mean_word_length': 5.302816901408451, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
DATA ANONYMIZATION WITH SPECIALIZED RING SIGNATURE TECHNIQUE FOR PRESERVING PRIVACY IN BIG DATA

Sharing of data has been greatly increased nowadays. Almost every individual started sharing their private data’s like health record and financial data, etc. For Big data processing framework which rely on cluster computers with a high performance computing platform some parallel programming tools like map-reduce has been used on a large number of computing node. To preserve privacy among the data being shared an effective anonymization technique is used. This paper focuses on describing the anonymization of the data by partitioning the attributes and applying appropriate map-reduce framework on the Hadoop Distributed File System. It also focuses on providing the authorized data and also preserving the identity of the authorized user by making use of an efficient Ring Signature concept.