Article Preview
Top1. Introduction
In the field of medicine, medical imaging constitutes an essential element in the diagnostic process. This is due mainly to the continuous development of biomedical imaging technology. In fact, these tools are considered as a clinical Diagnostic Support Tool (DST) to improve the quality of medical services. That is, hospitals and imaging centers produce large quantities of digital data to meet increasing demands. Therefore, scalable platforms along with software are required to manage patients’ medical data. Traditionally, healthcare organizations build and maintain local data centers to achieve this objective. Although Electronic Medical Record (EMR) systems are very beneficial for healthcare domain, they necessitate large investments in in-house applications and computational resources. Unfortunately, this has a negative impact on operating costs related to maintenance and license. To remedy this problem, cloud storage is a new way of delivering on-demand computing resources over the Internet. The primary aim of this concept is to facilitate the implementation and usage of the storage systems. More precisely, this model is designed to deliver a shared pool of configurable computing resources via the Internet. With this technology, the needed storage systems are provisioned and released to the clients with minimum management effort (Mell et al., 2009). At the same time, cloud storage relies on pay-per-use pricing model in which the consumers are charged based on cloud services utilization. Hence, cloud storage is an adequate solution to cut costs and increasing profits.
For these reasons, there has been a continuous demand for cloud services in the healthcare domain. Though cloud storage has many advantages, the adoption of this technology brings several security problems (Fabian et al., 2015; Anuja et al., 2015; Diago et al., 2014). In this regard, ensuring the confidentiality of medical data in the cloud environment is the major challenge facing this new paradigm, especially in healthcare sector. For instance, many frameworks and solutions have been proposed recently to meet security requirements. The main contribution of this paper is twofold. First, we present the state-of-the-art cloud storage implementation as well as techniques involved in data security. Second, we propose a framework that uses segmentation and watermarking techniques to secure medical images. Additionally, we use ABAC model to enforce data security policies.
The rest of this paper is organized as follows: Section 2 and 3 are meant to present and discuss existing solution to ensure the security of cloud storage. Section 4 and 5 provide a deep insight into privacy-preserving requirements to meet healthcare needs, especially data security. In section 6 and 7, we present the proposed framework as well as method used in data protection process. We end this paper in section 8 and 9 by concluding remarks and future work.