Efficient Unified Arithmetic for Hardware Cryptography

The basic arithmetic operations (i.e. addition, multiplication, and inversion) in finite fields, GF(q), where q = pk and p is a prime integer, have several applications in cryptography, such as RSA algorithm, Diffie-Hellman key exchange algorithm [1], the US federal Digital Signature Standard [2], elliptic curve cryptography [3, 4], and also recently identity based cryptography [5, 6]. Most popular finite fields that are heavily used in cryptographic applications due to elliptic curve based schemes are prime fields GF(p) and binary extension fields GF(2n). Recently, identity based cryptography based on pairing operations defined over elliptic curve points has stimulated a significant level of interest in the arithmetic of ternary extension fields, GF(3^n)

Research in the effective implementation of guidance computers with large scale arrays Interim report

Functional logic character implementation in breadboard design of NASA modular compute

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%

Efficient unified Montgomery inversion with multibit shifting

Computation of multiplicative inverses in finite fields GF(p) and GF(2/sup n/) is the most time-consuming operation in elliptic curve cryptography, especially when affine co-ordinates are used. Since the existing algorithms based on the extended Euclidean algorithm do not permit a fast software implementation, projective co-ordinates, which eliminate almost all of the inversion operations from the curve arithmetic, are preferred. In the paper, the authors demonstrate that affine co-ordinate implementation provides a comparable speed to that of projective co-ordinates with careful hardware realisation of existing algorithms for calculating inverses in both fields without utilising special moduli or irreducible polynomials. They present two inversion algorithms for binary extension and prime fields, which are slightly modified versions of the Montgomery inversion algorithm. The similarity of the two algorithms allows the design of a single unified hardware architecture that performs the computation of inversion in both fields. They also propose a hardware structure where the field elements are represented using a multi-word format. This feature allows a scalable architecture able to operate in a broad range of precision, which has certain advantages in cryptographic applications. In addition, they include statistical comparison of four inversion algorithms in order to help choose the best one amongst them for implementation onto hardware

Realizing arbitrary-precision modular multiplication with a fixed-precision multiplier datapath

Within the context of cryptographic hardware, the term scalability refers to the ability to process operands of any size, regardless of the precision of the underlying data path or registers. In this paper we present a simple yet effective technique for increasing the scalability of a fixed-precision Montgomery multiplier. Our idea is to extend the datapath of a Montgomery multiplier in such a way that it can also perform an ordinary multiplication of two n-bit operands (without modular reduction), yielding a 2n-bit result. This conventional (nxn->2n)-bit multiplication is then used as a “sub-routine” to realize arbitrary-precision Montgomery multiplication according to standard software algorithms such as Coarsely Integrated Operand Scanning (CIOS). We show that performing a 2n-bit modular multiplication on an n-bit multiplier can be done in 5n clock cycles, whereby we assume that the n-bit modular multiplication takes n cycles. Extending a Montgomery multiplier for this extra functionality requires just some minor modifications of the datapath and entails a slight increase in silicon area

Pipelined Two-Operand Modular Adders

Pipelined two-operand modular adder (TOMA) is one of basic components used in digital signal processing (DSP) systems that use the residue number system (RNS). Such modular adders are used in binary/residue and residue/binary converters, residue multipliers and scalers as well as within residue processing channels. The design of pipelined TOMAs is usually obtained by inserting an appriopriate number of latch layers inside a nonpipelined TOMA structure. Hence their area is also determined by the number of latches and the delay by the number of latch layers. In this paper we propose a new pipelined TOMA that is based on a new TOMA, that has the smaller area and smaller delay than other known structures. Comparisons are made using data from the very large scale of integration (VLSI) standard cell library

Hardware implementation of elliptic curve Diffie-Hellman key agreement scheme in GF(p)

With the advent of technology there are many applications that require secure communication. Elliptic Curve Public-key Cryptosystems are increasingly becoming popular due to their small key size and efficient algorithm. Elliptic curves are widely used in various key exchange techniques including Diffie-Hellman Key Agreement scheme. Modular multiplication and modular division are one of the basic operations in elliptic curve cryptography. Much effort has been made in developing efficient modular multiplication designs, however few works has been proposed for the modular division. Nevertheless, these operations are needed in various cryptographic systems. This thesis examines various scalable implementations of elliptic curve scalar multiplication employing multiplicative inverse or field division in GF(p) focussing mainly on modular divison architectures. Next, this thesis presents a new architecture for modular division based on the variant of Extended Binary GCD algorithm. The main contribution at system level architecture to the modular division unit is use of counters in place of shift registers that are basis of the algorithm and modifying the algorithm to introduce a modular correction unit for the output logic. This results in 62% increase in speed with respect to a prototype design. Finally, using the modular division architecture an Elliptic Curve ALU in GF(p) was implemented which can be used as the core arithmetic unit of an elliptic curve processor. The resulting architecture was targeted to Xilinx Vertex2v6000-bf957 FPGA device and can be implemented for different elliptic curves for almost all practical values of field p. The frequency of the ALU is 58.8 MHz for 128-bits utilizing 20% of the device at 27712 gates which is 30% faster than a prototype implementation with a 2% increase in area utilization. The ALU was tested to perform Diffie-Hellman Key Agreement Scheme and is suitable for other public-key cryptographic algorithms

Programming Quantum Computers Using Design Automation

Recent developments in quantum hardware indicate that systems featuring more than 50 physical qubits are within reach. At this scale, classical simulation will no longer be feasible and there is a possibility that such quantum devices may outperform even classical supercomputers at certain tasks. With the rapid growth of qubit numbers and coherence times comes the increasingly difficult challenge of quantum program compilation. This entails the translation of a high-level description of a quantum algorithm to hardware-specific low-level operations which can be carried out by the quantum device. Some parts of the calculation may still be performed manually due to the lack of efficient methods. This, in turn, may lead to a design gap, which will prevent the programming of a quantum computer. In this paper, we discuss the challenges in fully-automatic quantum compilation. We motivate directions for future research to tackle these challenges. Yet, with the algorithms and approaches that exist today, we demonstrate how to automatically perform the quantum programming flow from algorithm to a physical quantum computer for a simple algorithmic benchmark, namely the hidden shift problem. We present and use two tool flows which invoke RevKit. One which is based on ProjectQ and which targets the IBM Quantum Experience or a local simulator, and one which is based on Microsoft's quantum programming language Q$\#$.Comment: 10 pages, 10 figures. To appear in: Proceedings of Design, Automation and Test in Europe (DATE 2018

Comparison of Scalable Montgomery Modular Multiplication Implementations Embedded in Reconfigurable Hardware

International audienceThis paper presents a comparison of possible approaches for an efficient implementation of Multiple-word radix-2 Montgomery Modular Multiplication (MM) on modern Field Programmable Gate Arrays (FPGAs). The hardware implementation of MM coprocessor is fully scalable what means that it can be reused in order to generate long-precision results independently on the word length of the originally proposed coprocessor. The first of analyzed implementations uses a data path based on traditionally used redundant carry-save adders, the second one exploits, in scalable designs not yet applied, standard carry-propagate adders with fast carry chain logic. As a control unit and a platform for purely software implementation an embedded soft-core processor Altera NIOS is employed. All implementations use large embedded memory blocks available in recent FPGAs. Speed and logic requirements comparisons are performed on the optimized software and combined hardware-software designs in Altera FPGAs. The issues of targeting a design specifically for a FPGA are considered taking into account the underlying architecture imposed by the target FPGA technology. It is shown that the coprocessors based on carry-save adders and carry-propagate adders provide comparable results in constrained FPGA implementations but in case of carry-propagate logic, the solution requires less embedded memory and provides some additional implementation advantages presented in the paper