Analysis of ISO/IEEE 11073 built-in security and its potential IHE-based extensibility.

The ISO/IEEE 11073 standard for Personal Health Devices (X73PHD) aims to ensure interoperability between Personal Health Devices and aggregators-e.g. health appliances, routers-in ambulatory setups. The Integrating the Healthcare Enterprise (IHE) initiative promotes the coordinated use of different standards in healthcare systems (e.g. Personal/Electronic Health Records, alert managers, Clinical Decision Support Systems) by defining profiles intended for medical use cases. X73PHD provides a robust syntactic model and a comprehensive terminology, but it places limited emphasis on security and on interoperability with IHE-compliant systems and frameworks. However, the implementation of eHealth/mHealth applications in environments such as health and fitness monitoring, independent living and disease management (i.e. the X73PHD domains) increasingly requires features such as secure connections to mobile aggregators-e.g. smartphones, tablets-, the sharing of devices among different users with privacy, and interoperability with certain IHE-compliant healthcare systems. This work proposes a comprehensive IHE-based X73PHD extension consisting of additive layers adapted to different eHealth/mHealth applications, after having analyzed the features of X73PHD (especially its built-in security), IHE profiles related with these applications and other research works. Both the new features proposed for each layer and the procedures to support them have been carefully chosen to minimize the impact on X73PHD, on its architecture (in terms of delays and overhead) and on its framework. Such implications are thoroughly analyzed in this paper. As a result, an extended model of X73PHD is proposed, preserving its essential features while extending them with added value.

Introducing keytagging, a novel technique for the protection of medical image-based tests.

This paper introduces keytagging, a novel technique to protect medical image-based tests by implementing image authentication, integrity control and location of tampered areas, private captioning with role-based access control, traceability and copyright protection. It relies on the association of tags (binary data strings) to stable, semistable or volatile features of the image, whose access keys (called keytags) depend on both the image and the tag content. Unlike watermarking, this technique can associate information to the most stable features of the image without distortion. Thus, this method preserves the clinical content of the image without the need for assessment, prevents eavesdropping and collusion attacks, and obtains a substantial capacity-robustness tradeoff with simple operations. The evaluation of this technique, involving images of different sizes from various acquisition modalities and image modifications that are typical in the medical context, demonstrates that all the aforementioned security measures can be implemented simultaneously and that the algorithm presents good scalability. In addition to this, keytags can be protected with standard Cryptographic Message Syntax and the keytagging process can be easily combined with JPEG2000 compression since both share the same wavelet transform. This reduces the delays for associating keytags and retrieving the corresponding tags to implement the aforementioned measures to only ≃30 and ≃90ms respectively. As a result, keytags can be seamlessly integrated within DICOM, reducing delays and bandwidth when the image test is updated and shared in secure architectures where different users cooperate, e.g. physicians who interpret the test, clinicians caring for the patient and researchers.

Secure information embedding into 1D biomedical signals based on SPIHT.

This paper proposes an encoding system for 1D biomedical signals that allows embedding metadata and provides security and privacy. The design is based on the analysis of requirements for secure and efficient storage, transmission and access to medical tests in e-health environment. This approach uses the 1D SPIHT algorithm to compress 1D biomedical signals with clinical quality, metadata embedding in the compressed domain to avoid extra distortion, digital signature to implement security and attribute-level encryption to support Role-Based Access Control. The implementation has been extensively tested using standard electrocardiogram and electroencephalogram databases (MIT-BIH Arrhythmia, MIT-BIH Compression and SCCN-EEG), demonstrating high embedding capacity (e.g. 3 KB in resting ECGs, 200 KB in stress tests, 30 MB in ambulatory ECGs), short delays (2-3.3s in real-time transmission) and compression of the signal (by ≃3 in real-time transmission, by ≃5 in offline operation) despite of the embedding of security elements and metadata to enable e-health services.

A robust and simple security extension for the medical standard SCP-ECG.

This paper proposes a SCP-ECG security extension after having analyzed the features of this standard, its security requirements and the current measures implemented by other medical protocols. Our approach permits SCP-ECG files to be stored safely and proper access to be granted (or denied) to users for different purposes: interpretation of the test, consultation, clinical research or teaching. The access privileges are scaled by means of role-based profiles supported by cryptographic elements (ciphering, digital certificates and digital signatures). These elements are arranged as metadata into a new section which extends the protocol and protects the remaining sections. The application built to implement this approach has been extensively tested, showing its capacity to authenticate users and to protect the integrity of files and the privacy of sensitive data, with a low impact on file size and access time. In addition, this solution is compatible with any version of the SCP-ECG and can be easily integrated into e-health platforms.