A data partitioning and scrambling method to secure cloud storage with healthcare applications
Shu‐Di Bao, Yang Lu, Yan-Kai Yang, Chunyan Wang, Meng Chen, Guang‐Zhong Yang · 2015
With increasing use of cloud storage for healthcare applications, potential security risks and the need for enhanced security solutions are becoming a pressing issue for clinical adoption. In this paper, a data partitioning and scrambling method at the application layer is proposed for healthcare data, where a tiny part of the original data is used to scramble the remaining data without any cryptographic key, and the former is kept locally while the latter under extra protection is sent to cloud platforms. Theoretical and experimental analyses have been carried out to demonstrate the security performance of the proposed method, which can be easily deployed in any existing communication systems as an add-on for security.