1,984 research outputs found
Computational and Energy Costs of Cryptographic Algorithms on Handheld Devices
Networks are evolving toward a ubiquitous model in which heterogeneous
devices are interconnected. Cryptographic algorithms are required for developing security
solutions that protect network activity. However, the computational and energy limitations
of network devices jeopardize the actual implementation of such mechanisms. In this
paper, we perform a wide analysis on the expenses of launching symmetric and asymmetric
cryptographic algorithms, hash chain functions, elliptic curves cryptography and pairing
based cryptography on personal agendas, and compare them with the costs of basic operating
system functions. Results show that although cryptographic power costs are high and such
operations shall be restricted in time, they are not the main limiting factor of the autonomy
of a device
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
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Memory-Based High-Level Synthesis Optimizations Security Exploration on the Power Side-Channel
High-level synthesis (HLS) allows hardware designers to think algorithmically and not worry about low-level, cycle-by-cycle details. This provides the ability to quickly explore the architectural design space and tradeoffs between resource utilization and performance. Unfortunately, security evaluation is not a standard part of the HLS design flow. In this article, we aim to understand the effects of memory-based HLS optimizations on power side-channel leakage. We use Xilinx Vivado HLS to develop different cryptographic cores, implement them on a Spartan-6 FPGA, and collect power traces. We evaluate the designs with respect to resource utilization, performance, and information leakage through power consumption. We have two important observations and contributions. First, the choice of resource optimization directive results in different levels of side-channel vulnerabilities. Second, the partitioning optimization directive can greatly compromise the hardware cryptographic system through power side-channel leakage due to the deployment of memory control logic. We describe an evaluation procedure for power side-channel leakage and use it to make best-effort recommendations about how to design more secure architectures in the cryptographic domain
A Study of IEEE 802.15.4 Security Framework for Wireless Body Area Network
A Wireless Body Area Network (WBAN) is a collection of low-power and
lightweight wireless sensor nodes that are used to monitor the human body
functions and the surrounding environment. It supports a number of innovative
and interesting applications, including ubiquitous healthcare and Consumer
Electronics (CE) applications. Since WBAN nodes are used to collect sensitive
(life-critical) information and may operate in hostile environments, they
require strict security mechanisms to prevent malicious interaction with the
system. In this paper, we first highlight major security requirements and
Denial of Service (DoS) attacks in WBAN at Physical, Medium Access Control
(MAC), Network, and Transport layers. Then we discuss the IEEE 802.15.4
security framework and identify the security vulnerabilities and major attacks
in the context of WBAN. Different types of attacks on the Contention Access
Period (CAP) and Contention Free Period (CFP) parts of the superframe are
analyzed and discussed. It is observed that a smart attacker can successfully
corrupt an increasing number of GTS slots in the CFP period and can
considerably affect the Quality of Service (QoS) in WBAN (since most of the
data is carried in CFP period). As we increase the number of smart attackers
the corrupted GTS slots are eventually increased, which prevents the legitimate
nodes to utilize the bandwidth efficiently. This means that the direct
adaptation of IEEE 802.15.4 security framework for WBAN is not totally secure
for certain WBAN applications. New solutions are required to integrate high
level security in WBAN.Comment: 14 pages, 7 figures, 2 table
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