On a Formal and User-friendly Linguistic Approach to Access Control of Electronic Health Data

The importance of the exchange of Electronic Health Records (EHRs) between hospitals has been recognized by governments and institutions. Due to the sensitivity of data exchanged, only mature standards and implementations can be chosen to operate. This exchange process is of course under the control of the patient, who decides who has the rights to access her personal healthcare data and who has not, by giving her personal privacy consent. Patients’ privacy consent is regulated by local legislations, which can vary frequently from region to region. The technology implementing such privacy aspects must be highly adaptable, often resulting in complex security scenarios that cannot be easily managed by patients and software designers. To overcome such security problems, we advocate the use of a linguistic approach that relies on languages for expressing policies with solid mathematical foundations. Our approach bases on FACPL, a policy language we have intentionally designed by taking inspiration from OASIS XACML, the de-facto standard used in all projects covering secure EHRs transmission protected by patients’ privacy consent. FACPL can express policies similar to those expressible by XACML but, differently from XACML, it has an intuitive syntax, a formal semantics and easy to use software tools supporting policy development and enforcement. In this paper, we present the potentialities of our approach and outline ongoing work

Secure Management of Personal Health Records by Applying Attribute-Based Encryption

The confidentiality of personal health records is a major problem when patients use commercial Web-based systems to store their health data. Traditional access control mechanisms, such as Role-Based Access Control, have several limitations with respect to enforcing access control policies and ensuring data confidentiality. In particular, the data has to be stored on a central server locked by the access control mechanism, and the data owner loses control on the data from the moment when the data is sent to the requester. Therefore, these mechanisms do not fulfil the requirements of data outsourcing scenarios where the third party storing the data should not have access to the plain data, and it is not trusted to enforce access control policies. In this paper, we describe a new approach which enables secure storage and controlled sharing of patient’s health records in the aforementioned scenarios. A new variant of a ciphertext-policy attribute-based encryption scheme is proposed to enforce patient/organizational access control policies such that everyone can download the encrypted data but only authorized users from the social domain (e.g. family, friends, or fellow patients) or authorized users from the professional\ud domain (e.g. doctors or nurses) are allowed to decrypt it

A standard-driven communication protocol for disconnected clinics in rural areas

The importance of the Electronic Health Record (EHR), which stores all healthcare-related data belonging to a patient, has been recognized in recent years by governments, institutions, and industry. Initiatives like Integrating the Healthcare Enterprise (IHE) have been developed for the definition of standard methodologies for secure and interoperable EHR exchanges among clinics and hospitals. Using the requisites specified by these initiatives, many large-scale projects have been set up to enable healthcare professionals to handle patients' EHRs. Applications deployed in these settings are often considered safety-critical, thus ensuring such security properties as confidentiality, authentication, and authorization is crucial for their success. In this paper, we propose a communication protocol, based on the IHE specifications, for authenticating healthcare professionals and assuring patients' safety in settings where no network connection is available, such as in rural areas of some developing countries. We define a specific threat model, driven by the experience of use cases covered by international projects, and prove that an intruder cannot cause damages to the safety of patients and their data by performing any of the attacks falling within this threat model. To demonstrate the feasibility and effectiveness of our protocol, we have fully implemented it

Privacy provision in eHealth using external services

Privacy provision is a key issue for successful secure access to patients’ health information. Current approaches do not always provide patients with the ability to define suitable rules to access to their information in a secure way. This paper presents an approach to give patients control over their information by means of external services. In this way, health information management and access control are kept independent and more secure.Postprint (published version

A flexible architecture for privacy-aware trust management

In service-oriented systems a constellation of services cooperate, sharing potentially sensitive information and responsibilities. Cooperation is only possible if the different participants trust each other. As trust may depend on many different factors, in a flexible framework for Trust Management (TM) trust must be computed by combining different types of information. In this paper we describe the TAS3 TM framework which integrates independent TM systems into a single trust decision point. The TM framework supports intricate combinations whilst still remaining easily extensible. It also provides a unified trust evaluation interface to the (authorization framework of the) services. We demonstrate the flexibility of the approach by integrating three distinct TM paradigms: reputation-based TM, credential-based TM, and Key Performance Indicator TM. Finally, we discuss privacy concerns in TM systems and the directions to be taken for the definition of a privacy-friendly TM architecture.\u

E-infrastructures fostering multi-centre collaborative research into the intensive care management of patients with brain injury

Clinical research is becoming ever more collaborative with multi-centre trials now a common practice. With this in mind, never has it been more important to have secure access to data and, in so doing, tackle the challenges of inter-organisational data access and usage. This is especially the case for research conducted within the brain injury domain due to the complicated multi-trauma nature of the disease with its associated complex collation of time-series data of varying resolution and quality. It is now widely accepted that advances in treatment within this group of patients will only be delivered if the technical infrastructures underpinning the collection and validation of multi-centre research data for clinical trials is improved. In recognition of this need, IT-based multi-centre e-Infrastructures such as the Brain Monitoring with Information Technology group (BrainIT - www.brainit.org) and Cooperative Study on Brain Injury Depolarisations (COSBID - www.cosbid.de) have been formed. A serious impediment to the effective implementation of these networks is access to the know-how and experience needed to install, deploy and manage security-oriented middleware systems that provide secure access to distributed hospital based datasets and especially the linkage of these data sets across sites. The recently funded EU framework VII ICT project Advanced Arterial Hypotension Adverse Event prediction through a Novel Bayesian Neural Network (AVERT-IT) is focused upon tackling these challenges. This chapter describes the problems inherent to data collection within the brain injury medical domain, the current IT-based solutions designed to address these problems and how they perform in practice. We outline how the authors have collaborated towards developing Grid solutions to address the major technical issues. Towards this end we describe a prototype solution which ultimately formed the basis for the AVERT-IT project. We describe the design of the underlying Grid infrastructure for AVERT-IT and how it will be used to produce novel approaches to data collection, data validation and clinical trial design is also presented

DRM and Privacy

Interrogating the relationship between copyright enforcement and privacy raises deeper questions about the nature of privacy and what counts, or ought to count, as privacy invasion in the age of networked digital technologies. This Article begins, in Part II, by identifying the privacy interests that individuals enjoy in their intellectual activities and exploring the different ways in which certain implementations of DRM technologies may threaten those interests. Part III considers the appropriate scope of legal protection for privacy in the context of DRM, and argues that both the common law of privacy and an expanded conception of consumer protection law have roles to play in protecting the privacy of information users. As Parts II and III demonstrate, consideration of how the theory and law of privacy should respond to the development and implementation of DRM technologies also raises the reverse question: How should the development and implementation of DRM technologies respond to privacy theory and law? As artifacts designed to regulate user behavior, DRM technologies already embody value choices. Might privacy itself become one of the values embodied in DRM design? Part IV argues that with some conceptual and procedural adjustments, DRM technologies and related standard-setting processes could be harnessed to preserve and protect privacy

Protocol for a randomized controlled trial examining multilevel prediction of response to behavioral activation and exposure-based therapy for generalized anxiety disorder.

BACKGROUND:Only 40-60% of patients with generalized anxiety disorder experience long-lasting improvement with gold standard psychosocial interventions. Identifying neurobehavioral factors that predict treatment success might provide specific targets for more individualized interventions, fostering more optimal outcomes and bringing us closer to the goal of "personalized medicine." Research suggests that reward and threat processing (approach/avoidance behavior) and cognitive control may be important for understanding anxiety and comorbid depressive disorders and may have relevance to treatment outcomes. This study was designed to determine whether approach-avoidance behaviors and associated neural responses moderate treatment response to exposure-based versus behavioral activation therapy for generalized anxiety disorder. METHODS/DESIGN:We are conducting a randomized controlled trial involving two 10-week group-based interventions: exposure-based therapy or behavioral activation therapy. These interventions focus on specific and unique aspects of threat and reward processing, respectively. Prior to and after treatment, participants are interviewed and undergo behavioral, biomarker, and neuroimaging assessments, with a focus on approach and avoidance processing and decision-making. Primary analyses will use mixed models to examine whether hypothesized approach, avoidance, and conflict arbitration behaviors and associated neural responses at baseline moderate symptom change with treatment, as assessed using the Generalized Anxiety Disorder-7 item scale. Exploratory analyses will examine additional potential treatment moderators and use data reduction and machine learning methods. DISCUSSION:This protocol provides a framework for how studies may be designed to move the field toward neuroscience-informed and personalized psychosocial treatments. The results of this trial will have implications for approach-avoidance processing in generalized anxiety disorder, relationships between levels of analysis (i.e., behavioral, neural), and predictors of behavioral therapy outcome. TRIAL REGISTRATION:The study was retrospectively registered within 21 days of first participant enrollment in accordance with FDAAA 801 with ClinicalTrials.gov, NCT02807480. Registered on June 21, 2016, before results