A Privacy-Preserving Model for Big Data

Abstract

In the past few years, the tremendous expansion in the usage of computer programs has resulted in a large amount of data, called “Big Data.” This leads to new challenges for storage, processing, and privacy-preserving. Meanwhile, organizations tend to collect more data about customers for subsequent processing to extract knowledge, resulting in potential threats to their confidentiality. This raises significant questions regarding the security and privacy of data in NoSQL databases. In this paper, a privacy-preserving model for big data protection is proposed, which could be applied to various types of NoSQL databases. This model addresses the challenges of securing NoSQL databases including the lack of predefined schema, the existence of different NoSQL database categories, and the potential threats due to data processing. It also guarantees properties of conditional roles, purposes, tasks, policies, and possible insider threats. Verification and validation for the model using a use case are introduced to demonstrate how it ensures privacy-preserving in NoSQL databases.