A Survey on Privacy-Preserving Data Publishing Models for Big Data
J. Jayapradha, M. D. Antony Arul Prakash · Advances in information security, privacy, and ethics book series · 2022
Big data deals with massive amounts of data with various characteristics and intricate structures. The vast amount of data collection in big data has led to lots of security and privacy threats. Big data evolution and the need for security and privacy in big data have been covered in the study. Big data taxonomy framework, the privacy laws, and acts have also been analyzed and studied. Various privacy-preserving data publishing models and their attack models have been thoroughly studied under the categories of 1) record linkage model, 2) attribute linkage model, 3) table linkage model, and 4) probabilistic model. Furthermore, the trade-off between privacy and utility, future directions, and inference from the study have been summarized. The study gives insights into various techniques in privacy-preserving data publishing to address the problems related to privacy in big data.