Imperceptible reversible watermarking of radiographic images based on quantum noise masking.

Background And Objective: Advances in information and communication technologies boost the sharing and remote access to medical images. Along with this evolution, needs in terms of data security are also increased. Watermarking can contribute to better protect images by dissimulating into their pixels some security attributes (e.

Sharing Health Big Data for Research - A Design by Use Cases: The INSHARE Platform Approach.

Sharing and exploiting Health Big Data (HBD) allow tackling challenges: data protection/governance taking into account legal, ethical, and deontological aspects enables trust, transparent and win-win relationship between researchers, citizens, and data providers. Lack of interoperability: compartmentalized and syntactically/semantica heterogeneous data. INSHARE project using experimental proof of concept explores how recent technologies overcome such issues.

An end to end secure CBIR over encrypted medical database.

In this paper, we propose a new secure content based image retrieval (SCBIR) system adapted to the cloud framework. This solution allows a physician to retrieve images of similar content within an outsourced and encrypted image database, without decrypting them. Contrarily to actual CBIR approaches in the encrypted domain, the originality of the proposed scheme stands on the fact that the features extracted from the encrypted images are themselves encrypted.

Computed Tomography Image Origin Identification Based on Original Sensor Pattern Noise and 3-D Image Reconstruction Algorithm Footprints.

In this paper, we focus on the "blind" identification of the computed tomography (CT) scanner that has produced a CT image. To do so, we propose a set of noise features derived from the image chain acquisition and which can be used as CT-scanner footprint. Basically, we propose two approaches.

Content-based image retrieval in homomorphic encryption domain.

In this paper, we propose a secure implementation of a content-based image retrieval (CBIR) method that makes possible diagnosis aid systems to work in externalized environment and with outsourced data as in cloud computing. This one works with homomorphic encrypted images from which it extracts wavelet based image features next used for subsequent image comparison. By doing so, our system allows a physician to retrieve the most similar images to a query image in an outsourced database while preserving data confidentiality.

Secure public cloud platform for medical images sharing.

Cloud computing promises medical imaging services offering large storage and computing capabilities for limited costs. In this data outsourcing framework, one of the greatest issues to deal with is data security. To do so, we propose to secure a public cloud platform devoted to medical image sharing by defining and deploying a security policy so as to control various security mechanisms.

A joint encryption/watermarking system for verifying the reliability of medical images.

In this paper, we propose a joint encryption/water-marking system for the purpose of protecting medical images. This system is based on an approach which combines a substitutive watermarking algorithm, the quantization index modulation, with an encryption algorithm: a stream cipher algorithm (e.g.

A joint encryption/watermarking algorithm for verifying the reliability of medical images: application to echographic images.

In this paper we propose a joint encryption/watermarking algorithm for the purpose of protecting medical images. The proposed solution gives access to the outcomes of the image integrity and of its origins as its attachment to one patient even if the image is stored encrypted. In this study, the given solution combines the RC4 stream cipher and two substitutive watermarking modulations: the Least Significant Bit Method and the Quantization Index Modulation.