3,587 research outputs found
KLEIN: A New Family of Lightweight Block Ciphers
Resource-efficient cryptographic primitives become fundamental for realizing both security and efficiency in embedded systems like RFID tags and sensor nodes. Among those primitives, lightweight block cipher plays a major role as a building block for security protocols. In this paper, we describe a new family of lightweight block ciphers named KLEIN, which is designed for resource-constrained devices such as wireless sensors and RFID tags. Compared to the related proposals, KLEIN has advantage in the software performance on legacy sensor platforms, while in the same time its hardware implementation can also be compact
An IoT Endpoint System-on-Chip for Secure and Energy-Efficient Near-Sensor Analytics
Near-sensor data analytics is a promising direction for IoT endpoints, as it
minimizes energy spent on communication and reduces network load - but it also
poses security concerns, as valuable data is stored or sent over the network at
various stages of the analytics pipeline. Using encryption to protect sensitive
data at the boundary of the on-chip analytics engine is a way to address data
security issues. To cope with the combined workload of analytics and encryption
in a tight power envelope, we propose Fulmine, a System-on-Chip based on a
tightly-coupled multi-core cluster augmented with specialized blocks for
compute-intensive data processing and encryption functions, supporting software
programmability for regular computing tasks. The Fulmine SoC, fabricated in
65nm technology, consumes less than 20mW on average at 0.8V achieving an
efficiency of up to 70pJ/B in encryption, 50pJ/px in convolution, or up to
25MIPS/mW in software. As a strong argument for real-life flexible application
of our platform, we show experimental results for three secure analytics use
cases: secure autonomous aerial surveillance with a state-of-the-art deep CNN
consuming 3.16pJ per equivalent RISC op; local CNN-based face detection with
secured remote recognition in 5.74pJ/op; and seizure detection with encrypted
data collection from EEG within 12.7pJ/op.Comment: 15 pages, 12 figures, accepted for publication to the IEEE
Transactions on Circuits and Systems - I: Regular Paper
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
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