26-06-2013, 03:12 PM
SPOC: A Secure and Privacy-preserving Opportunistic Computing Framework for Mobile-Healthcare Emergency
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Abstract
With the pervasiveness of smart phones and the advance of wireless body sensor networks (BSNs), mobile Healthcare
(m-Healthcare), which extends the operation of Healthcare provider into a pervasive environment for better health monitoring, has
attracted considerable interest recently. However, the flourish of m-Healthcare still faces many challenges including information security
and privacy preservation. In this paper, we propose a secure and privacy-preserving opportunistic computing framework, called SPOC,
for m-Healthcare emergency. With SPOC, smart phone resources including computing power and energy can be opportunistically
gathered to process the computing-intensive personal health information (PHI) during m-Healthcare emergency with minimal privacy
disclosure. In specific, to leverage the PHI privacy disclosure and the high reliability of PHI process and transmission in m-Healthcare
emergency, we introduce an efficient user-centric privacy access control in SPOC framework, which is based on an attribute-based
access control and a new privacy-preserving scalar product computation (PPSPC) technique, and allows a medical user to decide who
can participate in the opportunistic computing to assist in processing his overwhelming PHI data. Detailed security analysis shows
that the proposed SPOC framework can efficiently achieve user-centric privacy access control in m-Healthcare emergency. In addition,
performance evaluations via extensive simulations demonstrate the SPOC’s effectiveness in term of providing high reliable PHI process
and transmission while minimizing the privacy disclosure during m-Healthcare emergency.
INTRODUCTION
In our aging society, mobile Healthcare (m-Healthcare) system
has been envisioned as an important application of pervasive
computing to improve health care quality and save lives, where
miniaturized wearable and implantable body sensor nodes
and smartphones are utilized to provide remote healthcare
monitoring to people who have chronic medical conditions
such as diabetes and heart disease [1], [2], [3], [4], [5].
Specifically, in an m-Healthcare system, medical users are
no longer needed to be monitored within home or hospital
environments. Instead, after being equipped with smartphone
and wireless body sensor network (BSN) formed by body
sensor nodes, medical users can walk outside and receive the
high-quality healthcare monitoring from medical professionals
anytime and anywhere.
MODELS AND DESIGN GOAL
In this section, we formalize the system model and security
model, and identify our design goal as well.
System Model
In our system model, we consider a trusted authority (TA)
and a group of l medical users U = {U1, U2, · · · , Ul},
as shown in Fig. 2. TA is a trustable and powerful entity
located at healthcare center, which is mainly responsible for
the management of the whole m-Healthcare system, e.g.,
initializing the system, equipping proper body sensor nodes
and key materials to medical users. Each medical user Ui ∈ U
is equipped with personal BSN and smartphone, which can
periodically collect PHI and report them to the healthcare
center for achieving better health care quality. Unlike in-bed
patients at home or hospital [16], [17], [18], medical users
U in our model are considered as mobile ones, i.e., walking
outside [19].
Security Model
Opportunistic computing can enhance the reliability for highintensive
PHI process and transmission in m-Healthcare emergency.
However, since PHI is very sensitive, a medical user,
even in emergency, will not expect to disclose his PHI to all
passing-by medical users. Instead, he may only disclose his
PHI to those medical users who have some similar symptoms
with him. In this case, the emergency situation can be handled
by opportunistic computing with minimal privacy disclosure.
Specifically, in our security model, we essentially define
two-phase privacy access control in opportunistic computing,
which are required for achieving high-reliable PHI process and
transmission in m-Healthcare emergency, as shown in Fig. 3.
Design Goal
Our design goal is to develop a secure and privacy-preserving
opportunistic computing framework to provide high reliability
of PHI process and transmission while minimizing PHI privacy
disclosure in m-Healthcare emergency. Specifically, we i)
apply opportunistic computing in m-Healthcare emergency to
achieve high-reliability of PHI process and transmission; and
ii) develop user-centric privacy access control to minimize the
PHI privacy disclosure.
PROPOSED SPOC FRAMEWORK
In this section, we propose our SPOC framework, which consists
of three parts: system initialization, user-centric privacy
access control for m-Healthcare emergency, and analysis of
opportunistic computing in m-Healthcare emergency. Before
describing them, we first review the bilinear pairing technique
[21], [22], [23], [24], which serves as the basis of the proposed
SPOC framework.
RELATED WORKS
Opportunistic computing: The study of opportunistic computing
has gained the great interest from the research community
recently, and we briefly review some of them related to our
work [7], [8], [9], [10]. In [7], Avvenuti et al. introduce the
opportunistic computing paradigm in wireless sensor network
to solve the problem of storing and executing an application
that exceeds the memory resources available on a single
sensor node. Especially, their solution is based on the idea
of partitioning the application code into a number of opportunistically
cooperating modules, and each node contributes to
the execution of the original application by running a subset of
the application tasks and providing service to the neighboring
nodes. In [8], Passarella et al. evaluate the performance of
service execution in opportunistic computing. Specifically,
they first abstract resources in pervasive computing as services,
that are opportunistically contributed by providers and invoked
by seekers. Then, they present a complete analytical model
to depict the service invocation process between seekers and
providers, and derive the optimal number of replicas to be
spawned on encountered nodes, in order to minimize the
execution time and optimize the computational and bandwidth
resources used.
CONCLUSIONS
In this paper, we have proposed a secure and privacypreserving
opportunistic computing (SPOC) framework for
m-Healthcare emergency, which mainly exploits how to use
opportunistic computing to achieve high reliability of PHI
process and transmission in emergency while minimizing.