Lightweight Selective Encryption for Social Data Protection Based on EBCOT Coding - Qiu, Han; Qiu, Meikang; Liu, Meiqin; Ming, Zhong (IEEE transactions on computational social systems, 2020)
Online social media today has a large number of users and has become a huge platform to collect and share the social data generated by the end users. In addition, based on the development of social applications, the social sensing system has been greatly developed to generate, transmit, and store, which is helping the prosperous of the social computing systems. However, the violation of the security of end users' social data stored and shared through the social computing system becomes a serious and urgent issue. The data protection on social media platforms is very different compared with the scenario of the traditional encryption algorithms, and most of the existing schemes are not suitable for data protection in the current social sensing and data-sharing system. In this article, we present a novel design based on the agnostic selective encryption concept to efficiently protect the social data based on the embedded block coding with optimized truncation system. By selectively encrypting only a small portion of the bitstreams in the middle layer of this coding system, a high level of protection and efficiency can both be achieved. We also experiment with our method on four common social data formats, and the security analysis tests are performed to verify the high protection level of our method.