Preserving the Privacy of Sensitive Data Using Bit-Coded-Sensitive Algorithm (BCSA)

Abstract

Organizations now deal with massive amounts of data. Data is collected from various points such as hospitals, credit card companies, and search engines. After collecting this voluminous data, it is published and shared for research. Data that is collected may have sensitive information that might be used to identify an individual and consequently lead to privacy violations when published. To address this challenge, privacy-preserving data publishing (PPDP) seeks to remove threats to privacy while ensuring that the necessary information is released for data mining. Various techniques have been proposed to solve the problems associated with sensitive information. One such technique is k-anonymity. This technique is the best and very efficient. However, it also leads to loss of information, reduces data utility, and works well only with static tables. In this paper, we proposed a technique that addresses the challenges of K-anonymity known as the Bit-Coded-Sensitive Algorithm (BCSA). This algo rithm is more efficient and effective and ensures that the privacy of the individual is preserved by avoiding disclosure, and linkages and at the same time ensuring the high quality and utility of data. BCSA first identifies the source of data and based on that, uses bits to code sensitive data with a key.