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Cross-organization or cross-domain cooperation takes place from time to
time in Electronic Health Record (EHR) system for necessary and high-quality
patient treatment. Cautious design of delegation mechanism must be in place as a
building block of cross-domain cooperation, since the cooperation inevitably
involves exchanging and sharing relevant patient data that are considered highly
private and confidential. The delegation mechanism grants permission to and
restricts access rights of a cooperating partner. Patients are unwilling to accept the
EHR system unless their health data are guaranteed proper use and disclosure,
which cannot be easily achieved without cross-domain authentication and
fine-grained access control. In addition, revocation of the delegated rights should
be possible at any time during the cooperation. In this paper, we propose a secure
EHR system, based on cryptographic constructions, to enable secure sharing of
sensitive patient data during cooperation and preserve patient data privacy. Our
EHR system further incorporates advanced mechanisms for fine-grained access
control, and on-demand revocation, as enhancements to the basic access control
offered by the delegation mechanism, and the basic revocation mechanism,
respectively. The proposed EHR system is demonstrated to fulfill objectives
specific to the cross-domain delegation scenario of interest.
TITLE: A Community-Driven Access Control Approach in Distributed IoT

The distributed Internet of Things is emerging in the literature as a new paradigm
for IoT where remotely controlled smart objects can act on their own to
sense/actuate, store, and interpret information either created by them or within the
surrounding environment. This paradigm calls for novel security and access control
mechanisms to enable smart objects with various resource limitations to evaluate a
claimed access right from external entities without relying on central authorization
systems. This article proposes utilizing a community-based structure to define the
notion of access rights in a distributed IoT environment. With this structure, within
a given community of smart objects sharing a common mission, access rights are to
be evaluated based on the community norms by smart objects with sufficient
resources on behalf of those with resource limitations. A novel, community-driven,
access control framework is proposed in addition to a prototype to demonstrate
access control granting in a user-friendly manner.

We propose a cognitive healthcare framework that adopts the Internet of Things
(IoT) cloud technologies. This framework uses smart sensors for communications
and deep learning for intelligent decision-making within the smart city perspective.
The cognitive and smart framework monitors patients’ state in real time and
provides accurate, timely, and high-quality healthcare services at low cost. To
assess the feasibility of the proposed framework, we present the experimental
results of an EEG pathology classification technique that uses deep learning. We
employ a range of healthcare smart sensors, including an EEG smart sensor, to
record and monitor multimodal healthcare data continuously. The EEG signals
from patients are transmitted via smart IoT devices to the cloud, where they are
processed and sent to a cognitive module. The system determines the state of the
patient by monitoring sensor readings, such as facial expressions, speech, EEG,
movements, and gestures. The real-time decision, based on which the future course
of action is taken, is made by the cognitive module. When information is
transmitted to the deep learning module, the EEG signals are classified as
pathologic or normal. The patient state monitoring and the EEG processing results
are shared with healthcare providers, who can then assess the patient’s condition
and provide emergency help if the patient is in a critical state. The proposed deep
learning model achieves better accuracy than the state-of-the-art systems.
TITLE: Internet-of-Things and Smart Homes for Elderly Healthcare: An End
User Perspective
YEAR: 2018
Although an Internet-of-Things-based smart home solution can provide an
improved and better approach to healthcare management, yet its end user adoption
is very low. With elderly people as the main target, these conservative users pose a
serious challenge to the successful implementation of smart home healthcare
services. The objective of this research was to develop and test a theoretical
framework empirically for determining the core factors that can affect the elderly
users’ acceptance of smart home services for healthcare. Accordingly, an online

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