A versatile Montgomery multiplier architecture with characteristic three support

We present a novel unified core design which is extended to realize Montgomery multiplication in the fields GF(2n), GF(3m), and GF(p). Our unified design supports RSA and elliptic curve schemes, as well as the identity-based encryption which requires a pairing computation on an elliptic curve. The architecture is pipelined and is highly scalable. The unified core utilizes the redundant signed digit representation to reduce the critical path delay. While the carry-save representation used in classical unified architectures is only good for addition and multiplication operations, the redundant signed digit representation also facilitates efficient computation of comparison and subtraction operations besides addition and multiplication. Thus, there is no need for a transformation between the redundant and the non-redundant representations of field elements, which would be required in the classical unified architectures to realize the subtraction and comparison operations. We also quantify the benefits of the unified architectures in terms of area and critical path delay. We provide detailed implementation results. The metric shows that the new unified architecture provides an improvement over a hypothetical non-unified architecture of at least 24.88%, while the improvement over a classical unified architecture is at least 32.07%

Speeding up a scalable modular inversion hardware architecture

The modular inversion is a fundamental process in several cryptographic systems. It can be computed in software or hardware, but hardware computation proven to be faster and more secure. This research focused on improving an old scalable inversion hardware architecture proposed in 2004 for finite field GF(p). The architecture has been made of two parts, a computing unit and a memory unit. The memory unit is to hold all the data bits of computation whereas the computing unit performs all the arithmetic operations in word (digit) by word bases known as scalable method. The main objective of this project was to investigate the cost and benefit of modifying the memory unit to include parallel shifting, which was one of the tasks of the scalable computing unit. The study included remodeling the entire hardware architecture removing the shifter from the scalable computing part embedding it in the memory unit instead. This modification resulted in a speedup to the complete inversion process with an area increase due to the new memory shifting unit. Quantitative measurements of the speed area trade-off have been investigated. The results showed that the extra hardware to be added for this modification compared to the speedup gained, giving the user the complete picture to choose from depending on the application need.the British council in Saudi Arabia, KFUPM, Dr. Tatiana Kalganova at the Electrical & Computer Engineering Department of Brunel University in Uxbridg

High Speed Hardware Architecture to Compute GF(p) Montgomery Inversion with Scalability Features

Modular inversion is a fundamental process in several cryptographic systems. It can be computed in software or hardware, but hardware computation has been proven to be faster and more secure. This research focused on improving an old scalable inversion hardware architecture proposed in 2004 for finite field GF(p). The architecture comprises two parts, a computing unit and a memory unit. The memory unit holds all the data bits of computation whereas the computing unit performs all the arithmetic operations in word (digit) by word bases such that the design is scalable. The main objective of this paper is to show the cost and benefit of modifying the memory unit to include shifting, which was previously one of the tasks of the scalable computing unit. The study included remodeling the entire hardware architecture removing the shifter from the scalable computing part and embedding it in the non-scalable memory unit instead. This modification resulted in a speedup to the complete inversion process with an area increase due to the new memory shifting unit. Several design schemes have been compared giving the user the complete picture to choose from depending on the application need

Customisable arithmetic hardware designs

Imperial Users onl

Low Power Elliptic Curve Cryptography

This M.S. thesis introduces new modulus scaling techniques for transforming a class of primes into special forms which enable efficient arithmetic. The scaling technique may be used to improve multiplication and inversion in finite fields. We present an efficient inversion algorithm that utilizes the structure of a scaled modulus. Our inversion algorithm exhibits superior performance to the Euclidean algorithm and lends itself to efficient hardware implementation due to its simplicity. Using the scaled modulus technique and our specialized inversion algorithm we develop an elliptic curve processor architecture. The resulting architecture successfully utilizes redundant representation of elements in GF(p) and provides a low-power, high speed, and small footprint specialized elliptic curve implementation. We also introduce a unified Montgomery multiplier architecture working on the extension fields GF(p), GF(2) and GF(3). With the increasing research activity for identity based encryption schemes, there has been an increasing need for arithmetic operations in field GF(3). Since we based our research on low-power and small footprint applications, we designed a unified architecture rather than having a seperate hardware for GF{3}. To the best of our knowledge, this is the first time a unified architecture was built working on three different extension fields

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

Hardware Implementations of Scalable and Unified Elliptic Curve Cryptosystem Processors

As the amount of information exchanged through the network grows, so does the demand for increased security over the transmission of this information. As the growth of computers increased in the past few decades, more sophisticated methods of cryptography have been developed. One method of transmitting data securely over the network is by using symmetric-key cryptography. However, a drawback of symmetric-key cryptography is the need to exchange the shared key securely. One of the solutions is to use public-key cryptography. One of the modern public-key cryptography algorithms is called Elliptic Curve Cryptography (ECC). The advantage of ECC over some older algorithms is the smaller number of key sizes to provide a similar level of security. As a result, implementations of ECC are much faster and consume fewer resources. In order to achieve better performance, ECC operations are often offloaded onto hardware to alleviate the workload from the servers' processors. The most important and complex operation in ECC schemes is the elliptic curve point multiplication (ECPM). This thesis explores the implementation of hardware accelerators that offload the ECPM operation to hardware. These processors are referred to as ECC processors, or simply ECPs. This thesis targets the efficient hardware implementation of ECPs specifically for the 15 elliptic curves recommended by the National Institute of Standards and Technology (NIST). The main contribution of this thesis is the implementation of highly efficient hardware for scalable and unified finite field arithmetic units that are used in the design of ECPs. In this thesis, scalability refers to the processor's ability to support multiple key sizes without the need to reconfigure the hardware. By doing so, the hardware does not need to be redesigned for the server to handle different levels of security. Unified refers to the ability of the ECP to handle both prime and binary fields. The resultant designs are valuable to the research community and industry, as a single hardware device is able to handle a wide range of ECC operations efficiently and at high speeds. Thus, improving the ability of network servers to handle secure transaction more quickly and improve productivity at lower costs

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))