24,324 research outputs found
TrustShadow: Secure Execution of Unmodified Applications with ARM TrustZone
The rapid evolution of Internet-of-Things (IoT) technologies has led to an
emerging need to make it smarter. A variety of applications now run
simultaneously on an ARM-based processor. For example, devices on the edge of
the Internet are provided with higher horsepower to be entrusted with storing,
processing and analyzing data collected from IoT devices. This significantly
improves efficiency and reduces the amount of data that needs to be transported
to the cloud for data processing, analysis and storage. However, commodity OSes
are prone to compromise. Once they are exploited, attackers can access the data
on these devices. Since the data stored and processed on the devices can be
sensitive, left untackled, this is particularly disconcerting.
In this paper, we propose a new system, TrustShadow that shields legacy
applications from untrusted OSes. TrustShadow takes advantage of ARM TrustZone
technology and partitions resources into the secure and normal worlds. In the
secure world, TrustShadow constructs a trusted execution environment for
security-critical applications. This trusted environment is maintained by a
lightweight runtime system that coordinates the communication between
applications and the ordinary OS running in the normal world. The runtime
system does not provide system services itself. Rather, it forwards requests
for system services to the ordinary OS, and verifies the correctness of the
responses. To demonstrate the efficiency of this design, we prototyped
TrustShadow on a real chip board with ARM TrustZone support, and evaluated its
performance using both microbenchmarks and real-world applications. We showed
TrustShadow introduces only negligible overhead to real-world applications.Comment: MobiSys 201
The Glasgow raspberry pi cloud: a scale model for cloud computing infrastructures
Data Centers (DC) used to support Cloud services
often consist of tens of thousands of networked machines under a single roof. The significant capital outlay required to replicate such infrastructures constitutes a major obstacle to practical implementation and evaluation of research in this domain. Currently, most research into Cloud computing relies on either limited software simulation, or the use of a testbed environments
with a handful of machines. The recent introduction of the
Raspberry Pi, a low-cost, low-power single-board computer, has made the construction of a miniature Cloud DCs more affordable.
In this paper, we present the Glasgow Raspberry Pi Cloud
(PiCloud), a scale model of a DC composed of clusters of
Raspberry Pi devices. The PiCloud emulates every layer of a
Cloud stack, ranging from resource virtualisation to network
behaviour, providing a full-featured Cloud Computing research and educational environment
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