Integrity Protection for Big Data Processing with Dynamic Redundancy Computation

Zhimin Gao, Nicholas DeSalvo, Pham Dang Khoa, Seung-Hun Kim, Lei Xu, Won Woo Ro, Rakesh M. Verma, Weidong Shi

Abstract: Big data is a hot topic and has found various applications in different areas such as scientific research, financial analysis, and market studies. The development of cloud computing technology provides an adequate platform for big data applications. No matter public or private, the outsourcing and sharing characteristics of the computation model make security a big concern for big data processing in the cloud. Most existing works focus on protection of data privacy but integrity protection of the processing procedure receives little attention, which may lead the big data application user to wrong conclusions and cause serious consequences. To address this challenge, we design an integrity protection solution for big data processing in cloud environments using reputation based redundancy computation. The implementation and experiment results show that the solution only adds limited cost to achieve integrity protection and is practical for real world applications.