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%

Novel algorithms and hardware architectures for Montgomery Multiplication over GF(p)

This report describes the design and implementation results in FPGAs of a scalable hardware architecture for computing modular multiplication in prime fields GF($p$), based on the Montgomery multiplication (MM) algorithm. Starting from an existing digit-serial version of the MM algorithm, a novel {\it digit-digit} based MM algorithm is derived and two hardware architectures that compute that algorithm are described. In the proposed approach, the input operands (multiplicand, multiplier and modulus) are represented using as radix $\beta = 2^k$. Operands of arbitrary size can be multiplied with modular reduction using almost the same hardware since the multiplier\u27s kernel module that performs the modular multiplication depends only on $k$. The novel hardware architectures proposed in this paper were verified by modeling them using VHDL and implementing them in the Xilinx FPGAs Spartan and Virtex5. Design trade-offs are analyzed considering different operand sizes commonly used in cryptography and different values for $k$. The proposed designs for MM are well suited to be implemented in modern FPGAs, making use of available dedicated multiplier and memory blocks reducing drastically the FPGA\u27s standard logic while keeping an acceptable performance compared with other implementation approaches. From the Virtex5 implementation, the proposed MM multiplier reaches a throughput of 242Mbps using only 219 FPGA slices and achieving a 1024-bit modular multiplication in 4.21$\mu$secs

Customisable arithmetic hardware designs

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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

Formal Analysis of Arithmetic Circuits using Computer Algebra - Verification, Abstraction and Reverse Engineering

Despite a considerable progress in verification and abstraction of random and control logic, advances in formal verification of arithmetic designs have been lagging. This can be attributed mostly to the difficulty in an efficient modeling of arithmetic circuits and datapaths without resorting to computationally expensive Boolean methods, such as Binary Decision Diagrams (BDDs) and Boolean Satisfiability (SAT), that require “bit blasting”, i.e., flattening the design to a bit-level netlist. Approaches that rely on computer algebra and Satisfiability Modulo Theories (SMT) methods are either too abstract to handle the bit-level nature of arithmetic designs or require solving computationally expensive decision or satisfiability problems. The work proposed in this thesis aims at overcoming the limitations of analyzing arithmetic circuits, specifically at the post-synthesized phase. It addresses the verification, abstraction and reverse engineering problems of arithmetic circuits at an algebraic level, treating an arithmetic circuit and its specification as a properly constructed algebraic system. The proposed technique solves these problems by function extraction, i.e., by deriving arithmetic function computed by the circuit from its low-level circuit implementation using computer algebraic rewriting technique. The proposed techniques work on large integer arithmetic circuits and finite field arithmetic circuits, up to 512-bit wide containing millions of logic gates

Unified field multiplier for GF(p) and GF(2 n) with novel digit encoding

In recent years, there has been an increase in demand for unified field multipliers for Elliptic Curve Cryptography in the electronics industry because they provide flexibility for customers to choose between Prime (GF(p)) and Binary (GF(2")) Galois Fields. Also, having the ability to carry out arithmetic over both GF(p) and GF(2") in the same hardware provides the possibility of performing any cryptographic operation that requires the use of both fields. The unified field multiplier is relatively future proof compared with multipliers that only perform arithmetic over a single chosen field. The security provided by the architecture is also very important. It is known that the longer the key length, the more susceptible the system is to differential power attacks due to the increased amount of data leakage. Therefore, it is beneficial to design hardware that is scalable, so that more data can be processed per cycle. Another advantage of designing a multiplier that is capable of dealing with long word length is improvement in performance in terms of delay, because less cycles are needed. This is very important because typical elliptic curve cryptography involves key size of 160 bits. A novel unified field radix-4 multiplier using Montgomery Multiplication for the use of G(p) and GF(2") has been proposed. This design makes use of the unexploited state in number representation for operation in GF(2") where all carries are suppressed. The addition is carried out using a modified (4:2) redundant adder to accommodate the extra 1 * state. The proposed adder and the partial product generator design are capable of radix-4 operation, which reduces the number of computation cycles required. Also, the proposed adder is more scalable than existing designs.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Unified field multiplier for GF(p) and GF(2 n) with novel digit encoding

In recent years, there has been an increase in demand for unified field multipliers for Elliptic Curve Cryptography in the electronics industry because they provide flexibility for customers to choose between Prime (GF(p)) and Binary (GF(2')) Galois Fields. Also, having the ability to carry out arithmetic over both GF(p) and GF(2') in the same hardware provides the possibility of performing any cryptographic operation that requires the use of both fields. The unified field multiplier is relatively future proof compared with multipliers that only perform arithmetic over a single chosen field. The security provided by the architecture is also very important. It is known that the longer the key length, the more susceptible the system is to differential power attacks due to the increased amount of data leakage. Therefore, it is beneficial to design hardware that is scalable, so that more data can be processed per cycle. Another advantage of designing a multiplier that is capable of dealing with long word length is improvement in performance in terms of delay, because less cycles are needed. This is very important because typical elliptic curve cryptography involves key size of 160 bits. A novel unified field radix-4 multiplier using Montgomery Multiplication for the use of G(p) and GF(2') has been proposed. This design makes use of the unexploited state in number representation for operation in GF(2') where all carries are suppressed. The addition is carried out using a modified (4:2) redundant adder to accommodate the extra 1 * state. The proposed adder and the partial product generator design are capable of radix-4 operation, which reduces the number of computation cycles required. Also, the proposed adder is more scalable than existing designs

UpWB: An Uncoupled Architecture Design for White-box Cryptography Using Vectorized Montgomery Multiplication

White-box cryptography (WBC) seeks to protect secret keys even if the attacker has full control over the execution environment. One of the techniques to hide the key is space hardness approach, which conceals the key into a large lookup table generated from a reliable small block cipher. Despite its provable security, space-hard WBC also suffers from heavy performance overhead when executed on general purpose hardware platform, hundreds of magnitude slower than conventional block ciphers. Specifically, recent studies adopt nested substitution permutation network (NSPN) to construct dedicated white-box block cipher [BIT16], whose performance is limited by a massive number of rounds, nested loop dependency and high-dimension dynamic maximal distance separable (MDS) matrices. To address these limitations, we put forward UpWB, an uncoupled and efficient accelerator for NSPN-structure WBC. We propose holistic optimization techniques across timing schedule, algorithms and operators. For the high-level timing schedule, we propose a fine-grained task partition (FTP) mechanism to decouple the parameteroriented nested loop with different trip counts. The FTP mechanism narrows down the idle time for synchronization and avoids the extra usage of FIFO, which efficiently increases the computation throughput. For the optimization of arithmetic operators, we devise a flexible and vectorized modular multiplier (VMM) based on the complexity-reduced Montgomery algorithm, which can process multi-precision variable data, multi-size matrix-vector multiplication and different irreducible polynomials. Then, a configurable matrix-vector multiplication (MVM) architecture with diagonal-major dataflow is presented to handle the dynamic MDS matrix. The multi-scale (Inv)Mixcolumns are also unified in a compact manner by intensively sharing the common sub-operations and customizing the constant multiplier. To verify the proposed methodology, we showcase the unified design implementation for three recent families of WBCs, including SPNbox-8/16/24/32, Yoroi-16/32 and WARX-16. Evaluated on FPGA platform, UpWB outperforms the optimized software counterpart (executed on 3.2 GHz Intel CPU with AES-NI and AVX2 instructions) by 7x to 30x in terms of computation throughput. Synthesized under TSMC 28nm technology, 36x to 164x improvement of computation throughput is achieved when UpWB operates at the maximum frequency of 1.3 GHz and consumes a modest area 0.14 mm2. Besides, the proposed VMM also offers about 30% improvement of area efficiency without pulling flexibility down when compared to state-of-the-art work