2,225 research outputs found
Throughput/Area-efficient ECC Processor Using Montgomery Point Multiplication on FPGA
High throughput while maintaining low resource is a key issue for elliptic curve cryptography (ECC) hardware implementations in many applications. In this brief, an ECC processor architecture over Galois fields is presented, which achieves the best reported throughput/area performance on field-programmable gate array (FPGA) to date. A novel segmented pipelining digit serial multiplier is developed to speed up ECC point multiplication. To achieve low latency, a new combined algorithm is developed for point addition and point doubling with careful scheduling. A compact and flexible distributed-RAM-based memory unit design is developed to increase speed while keeping area low. Further optimizations were made via timing constraints and logic level modifications at the implementation level. The proposed architecture is implemented on Virtex4 (V4), Virtex5 (V5), and Virtex7 (V7) FPGA technologies and, respectively, achieved throughout/slice figures of 19.65, 65.30, and 64.48 (106/(Seconds × Slices))
Efficient Implementation on Low-Cost SoC-FPGAs of TLSv1.2 Protocol with ECC_AES Support for Secure IoT Coordinators
Security management for IoT applications is a critical research field, especially when taking into account the performance variation over the very different IoT devices. In this paper, we present high-performance client/server coordinators on low-cost SoC-FPGA devices for secure IoT data collection. Security is ensured by using the Transport Layer Security (TLS) protocol based on the TLS_ECDHE_ECDSA_WITH_AES_128_CBC_SHA256 cipher suite. The hardware architecture of the proposed coordinators is based on SW/HW co-design, implementing within the hardware accelerator core Elliptic Curve Scalar Multiplication (ECSM), which is the core operation of Elliptic Curve Cryptosystems (ECC). Meanwhile, the control of the overall TLS scheme is performed in software by an ARM Cortex-A9 microprocessor. In fact, the implementation of the ECC accelerator core around an ARM microprocessor allows not only the improvement of ECSM execution but also the performance enhancement of the overall cryptosystem. The integration of the ARM processor enables to exploit the possibility of embedded Linux features for high system flexibility. As a result, the proposed ECC accelerator requires limited area, with only 3395 LUTs on the Zynq device used to perform high-speed, 233-bit ECSMs in 413 µs, with a 50 MHz clock. Moreover, the generation of a 384-bit TLS handshake secret key between client and server coordinators requires 67.5 ms on a low cost Zynq 7Z007S device
Evaluating Built-in ECC of FPGA on-chip Memories for the Mitigation of Undervolting Faults
Voltage underscaling below the nominal level is an effective solution for
improving energy efficiency in digital circuits, e.g., Field Programmable Gate
Arrays (FPGAs). However, further undervolting below a safe voltage level and
without accompanying frequency scaling leads to timing related faults,
potentially undermining the energy savings. Through experimental voltage
underscaling studies on commercial FPGAs, we observed that the rate of these
faults exponentially increases for on-chip memories, or Block RAMs (BRAMs). To
mitigate these faults, we evaluated the efficiency of the built-in
Error-Correction Code (ECC) and observed that more than 90% of the faults are
correctable and further 7% are detectable (but not correctable). This
efficiency is the result of the single-bit type of these faults, which are then
effectively covered by the Single-Error Correction and Double-Error Detection
(SECDED) design of the built-in ECC. Finally, motivated by the above
experimental observations, we evaluated an FPGA-based Neural Network (NN)
accelerator under low-voltage operations, while built-in ECC is leveraged to
mitigate undervolting faults and thus, prevent NN significant accuracy loss. In
consequence, we achieve 40% of the BRAM power saving through undervolting below
the minimum safe voltage level, with a negligible NN accuracy loss, thanks to
the substantial fault coverage by the built-in ECC.Comment: 6 pages, 2 figure
Implementing a protected zone in a reconfigurable processor for isolated execution of cryptographic algorithms
We design and realize a protected zone inside a reconfigurable and extensible embedded RISC processor for isolated execution of cryptographic algorithms. The protected zone is a collection of processor subsystems such as functional units optimized for high-speed execution of integer operations, a small amount of local memory, and general and special-purpose registers. We outline the principles for secure software implementation of cryptographic algorithms
in a processor equipped with the protected zone. We also demonstrate the efficiency and effectiveness of the protected zone by implementing major cryptographic algorithms, namely RSA, elliptic curve cryptography, and AES in the protected zone. In terms of time efficiency, software implementations
of these three cryptographic algorithms outperform equivalent software implementations on similar processors reported in the literature. The protected zone is designed in such a modular fashion that it can easily be integrated into any RISC processor; its area overhead is considerably moderate in the sense that
it can be used in vast majority of embedded processors. The protected zone can also provide the necessary support to implement TPM functionality within the boundary of a processor
Optimizing Scrubbing by Netlist Analysis for FPGA Configuration Bit Classification and Floorplanning
Existing scrubbing techniques for SEU mitigation on FPGAs do not guarantee an
error-free operation after SEU recovering if the affected configuration bits do
belong to feedback loops of the implemented circuits. In this paper, we a)
provide a netlist-based circuit analysis technique to distinguish so-called
critical configuration bits from essential bits in order to identify
configuration bits which will need also state-restoring actions after a
recovered SEU and which not. Furthermore, b) an alternative classification
approach using fault injection is developed in order to compare both
classification techniques. Moreover, c) we will propose a floorplanning
approach for reducing the effective number of scrubbed frames and d),
experimental results will give evidence that our optimization methodology not
only allows to detect errors earlier but also to minimize the
Mean-Time-To-Repair (MTTR) of a circuit considerably. In particular, we show
that by using our approach, the MTTR for datapath-intensive circuits can be
reduced by up to 48.5% in comparison to standard approaches
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