Sensor network security for pervasive e‐health

Abstract

Ubiquitous 24/7 health monitoring systems based on wireless medical sensors are going to play a key role for pervasive e-health applications. These systems allow care givers to early detect and act on signs of patients' clinical deterioration improving quality of care in a reliable unobtrusive and cost effective way. Ensuring the privacy and security of the exchanged information is challenging in pervasive e-health environments due to the resource constraints of tiny wireless medical sensors and operational requirements such as user mobility, strict latency needs, or the multitude of parties involved in the system. This paper describes a comprehensive and practical security framework for these pervasive health monitoring systems. We distinguish three layers addressing the specific security needs at the patient area network, medical sensor network, and backend levels. Thereby our architecture accommodates the healthcare institution-centric approach predominant today while making provisions for the more patient-centric vision of pervasive e-health environments. The tailored security mechanisms for each individual layer as well as their interworking are presented and evaluated in detail. The analysis shows that our proposed security framework allows the deployment of wireless medical sensor networks in a very efficient way. CopyrightThe pervasive use of MSNs and PANs presents very specific technical and operational features that challenge and have an impact on the design of the security architecture. Technical and operational featuresFirst, the WMSs can be resource constrained devices with just a few KB of memory, slow and short-word CPUs, and low-rate radios. Thus, security mechanism must be energy efficient, to minimize the memory needs especially RAM, and consuming negligible amount of computational and communication resources. Second, a key requirement for Figure 2. Overview of our system framework.

Ethics of the health-related internet of things: a narrative review

“…Chan et al 2009;Demiris 2009;Jea et al 2008;Mitseva et al 2008;Mittelstadt et al 2011;Tentori et al 2006;Tiwari et al 2010;Garde-Perik et al 2006;van Hoof et al 2007). At its narrowest, informational privacy can be equated with hiding personally identifiable data from unauthorised parties (Garcia-Morchon et al 2011;Ahamed et al 2007), and can be quantifiable (Srinivasan et al 2008). As health data are normally considered as particularly sensitive both in an ethical and legal sense (Baldini et al 2016), informational privacy is a central concern for the design and deployment of H-IoT, insofar as it contributes to gain control over the spread of information about the user's health status and history.…”

“…However, risks of re-identification of anonymised data through aggregation and re-purposing, and the tradeoff between the scientific or commercial value of data and de-identification must be taken seriously (Peppet 2014;Ebersold and Glass 2016;Jiya 2016;Baldini et al 2016). For both identifiable and de-identified data, policies restricting access to identifiable data (Subramaniam et al 2010;Bagüés et al 2007b;Garcia-Morchon et al 2011) only for acceptable purposes (Massacci et al 2009;Chakraborty et al 2011;Beaudin et al 2006) can address privacy risks. For instance, access can be agreed upon ahead of time for researchers depending on the study to be developed (Master et al 2014).…”

“…Essén 2008). Userend policies have been proposed as a solution which allows users to pre-define a customized level of privacy meeting their expectations (Friedewald et al 2007;Massacci et al 2009;Garcia-Morchon et al 2011). Privacy tools such as these are meant to enable users to freely move between and interact with a range of H-IoT systems without negotiating individual privacy agreements, while respecting the necessity of informed consent (cf.…”

Designing the Health-related Internet of Things: Ethical Principles and Guidelines

“…Features that provide users with control over data collection and transmission should be included in the design of H-IoT. These include simple on/off switches (or an online/offline mode), "consent sliders" to set at the time of use which data are collected and how they transmitted, and complex privacy policy management systems that allow users to select granularly what data to share, for what purposes, and with whom [37,71,72]. "Offline" privacy barriers such as physical walls can be replicated by requiring explicit action by users to upload or share data to publicly accessible locations.…”

Secure and efficient dynamic program update in wireless sensor networks

“…Recently, wireless sensor networks (WSNs) have attracted a great deal of research attention because of their wide range of potential applications including military, healthcare, and security . A typical sensor network usually has one base station that serves as the commander and data sink.…”