Area- Efficient VLSI Implementation of Serial-In Parallel-Out Multiplier Using Polynomial Representation in Finite Field GF(2m)

Finite field multiplier is mainly used in elliptic curve cryptography, error-correcting codes and signal processing. Finite field multiplier is regarded as the bottleneck arithmetic unit for such applications and it is the most complicated operation over finite field GF(2m) which requires a huge amount of logic resources. In this paper, a new modified serial-in parallel-out multiplication algorithm with interleaved modular reduction is suggested. The proposed method offers efficient area architecture as compared to proposed algorithms in the literature. The reduced finite field multiplier complexity is achieved by means of utilizing logic NAND gate in a particular architecture. The efficiency of the proposed architecture is evaluated based on criteria such as time (latency, critical path) and space (gate-latch number) complexity. A detailed comparative analysis indicates that, the proposed finite field multiplier based on logic NAND gate outperforms previously known resultsComment: 19 pages, 4 figure

Concurrent Error Detection in Finite Field Arithmetic Operations

With significant advances in wired and wireless technologies and also increased shrinking in the size of VLSI circuits, many devices have become very large because they need to contain several large units. This large number of gates and in turn large number of transistors causes the devices to be more prone to faults. These faults specially in sensitive and critical applications may cause serious failures and hence should be avoided. On the other hand, some critical applications such as cryptosystems may also be prone to deliberately injected faults by malicious attackers. Some of these faults can produce erroneous results that can reveal some important secret information of the cryptosystems. Furthermore, yield factor improvement is always an important issue in VLSI design and fabrication processes. Digital systems such as cryptosystems and digital signal processors usually contain finite field operations. Therefore, error detection and correction of such operations have become an important issue recently. In most of the work reported so far, error detection and correction are applied using redundancies in space (hardware), time, and/or information (coding theory). In this work, schemes based on these redundancies are presented to detect errors in important finite field arithmetic operations resulting from hardware faults. Finite fields are used in a number of practical cryptosystems and channel encoders/decoders. The schemes presented here can detect errors in arithmetic operations of finite fields represented in different bases, including polynomial, dual and/or normal basis, and implemented in various architectures, including bit-serial, bit-parallel and/or systolic arrays

Novel Single and Hybrid Finite Field Multipliers over GF(2m) for Emerging Cryptographic Systems

With the rapid development of economic and technical progress, designers and users of various kinds of ICs and emerging embedded systems like body-embedded chips and wearable devices are increasingly facing security issues. All of these demands from customers push the cryptographic systems to be faster, more efficient, more reliable and safer. On the other hand, multiplier over GF(2m) as the most important part of these emerging cryptographic systems, is expected to be high-throughput, low-complexity, and low-latency. Fortunately, very large scale integration (VLSI) digital signal processing techniques offer great facilities to design efficient multipliers over GF(2m). This dissertation focuses on designing novel VLSI implementation of high-throughput low-latency and low-complexity single and hybrid finite field multipliers over GF(2m) for emerging cryptographic systems. Low-latency (latency can be chosen without any restriction) high-speed pentanomial basis multipliers are presented. For the first time, the dissertation also develops three high-throughput digit-serial multipliers based on pentanomials. Then a novel realization of digit-level implementation of multipliers based on redundant basis is introduced. Finally, single and hybrid reordered normal basis bit-level and digit-level high-throughput multipliers are presented. To the authors knowledge, this is the first time ever reported on multipliers with multiple throughput rate choices. All the proposed designs are simple and modular, therefore suitable for VLSI implementation for various emerging cryptographic systems

Efficient and Low-complexity Hardware Architecture of Gaussian Normal Basis Multiplication over GF(2m) for Elliptic Curve Cryptosystems

In this paper an efficient high-speed architecture of Gaussian normal basis multiplier over binary finite field GF(2m) is presented. The structure is constructed by using regular modules for computation of exponentiation by powers of 2 and low-cost blocks for multiplication by normal elements of the binary field. Since the exponents are powers of 2, the modules are implemented by some simple cyclic shifts in the normal basis representation. As a result, the multiplier has a simple structure with a low critical path delay. The efficiency of the proposed structure is studied in terms of area and time complexity by using its implementation on Vertix-4 FPGA family and also its ASIC design in 180nm CMOS technology. Comparison results with other structures of the Gaussian normal basis multiplier verify that the proposed architecture has better performance in terms of speed and hardware utilization

Bit Serial Systolic Architectures for Multiplicative Inversion and Division over GF(2^m)

Systolic architectures are capable of achieving high throughput by maximizing pipelining and by eliminating global data interconnects. Recursive algorithms with regular data flows are suitable for systolization. The computation of multiplicative inversion using algorithms based on EEA (Extended Euclidean Algorithm) are particularly suitable for systolization. Implementations based on EEA present a high degree of parallelism and pipelinability at bit level which can be easily optimized to achieve local data flow and to eliminate the global interconnects which represent most important bottleneck in todays sub-micron design process. The net result is to have high clock rate and performance based on efficient systolic architectures. This thesis examines high performance but also scalable implementations of multiplicative inversion or field division over Galois fields GF(2m) in the specific case of cryptographic applications where field dimension m may be very large (greater than 400) and either m or defining irreducible polynomial may vary. For this purpose, many inversion schemes with different basis representation are studied and most importantly variants of EEA and binary (Stein's) GCD computation implementations are reviewed. A set of common as well as contrasting characteristics of these variants are discussed. As a result a generalized and optimized variant of EEA is proposed which can compute division, and multiplicative inversion as its subset, with divisor in either polynomial or triangular basis representation. Further results regarding Hankel matrix formation for double-basis inversion is provided. The validity of using the same architecture to compute field division with polynomial or triangular basis representation is proved. Next, a scalable unidirectional bit serial systolic array implementation of this proposed variant of EEA is implemented. Its complexity measures are defined and these are compared against the best known architectures. It is shown that assuming the requirements specified above, this proposed architecture may achieve a higher clock rate performance w. r. t. other designs while being more flexible, reliable and with minimum number of inter-cell interconnects. The main contribution at system level architecture is the substitution of all counter or adder/subtractor elements with a simpler distributed and free of carry propagation delays structure. Further a novel restoring mechanism for result sequences of EEA is proposed using a double delay element implementation. Finally, using this systolic architecture a CMD (Combined Multiplier Divider) datapath is designed which is used as the core of a novel systolic elliptic curve processor. This EC processor uses affine coordinates to compute scalar point multiplication which results in having a very small control unit and negligible with respect to the datapath for all practical values of m. The throughput of this EC based on this bit serial systolic architecture is comparable with designs many times larger than itself reported previously

High-speed VLSI implementation of Digit-serial Gaussian normal basis Multiplication over GF(2m)

In this paper, by employing the logical effort technique an efficient and high-speed VLSI implementation of the digit-serial Gaussian normal basis multiplier is presented. It is constructed by using AND, XOR and XOR tree components. To have a low-cost implementation with low number of transistors, the block of AND gates are implemented by using NAND gates based on the property of the XOR gates in the XOR tree. To optimally decrease the delay and increase the drive ability of the circuit the logical effort method as an efficient method for sizing the transistors is employed. By using this method and also a 4-input XOR gate structure, the circuit is designed for minimum delay. The digit-serial Gaussian normal basis multiplier is implemented over two binary finite fields GF(2163) and GF(2233) in 0.18μm CMOS technology for three different digit sizes. The results show that the proposed structures, compared to previous structures, have been improved in terms of delay and area parameters

Design of a GF(64)-LDPC Decoder Based on the EMS Algorithm

International audienceThis paper presents the architecture, performance and implementation results of a serial GF(64)-LDPC decoder based on a reduced-complexity version of the Extended Min-Sum algorithm. The main contributions of this work correspond to the variable node processing, the codeword decision and the elementary check node processing. Post-synthesis area results show that the decoder area is less than 20% of a Virtex 4 FPGA for a decoding throughput of 2.95 Mbps. The implemented decoder presents performance at less than 0.7 dB from the Belief Propagation algorithm for different code lengths and rates. Moreover, the proposed architecture can be easily adapted to decode very high Galois Field orders, such as GF(4096) or higher, by slightly modifying a marginal part of the design

Efficient ASIC Architecture for Low Latency Classic McEliece Decoding

Post-quantum cryptography addresses the increasing threat that quantum computing poses to modern communication systems. Among the available “quantum-resistant” systems, the Classic McEliece key encapsulation mechanism (KEM) is positioned as a conservative choice with strong security guarantees. Building upon the code-based Niederreiter cryptosystem, this KEM enables high performance encapsulation and decapsulation and is thus ideally suited for applications such as the acceleration of server workloads. However, until now, no ASIC architecture is available for low latency computation of Classic McEliece operations. Therefore, the present work targets the design, implementation and optimization of a tailored ASIC architecture for low latency Classic McEliece decoding. An efficient ASIC design is proposed, which was implemented and manufactured in a 22 nm FDSOI CMOS technology node. We also introduce a novel inversionless architecture for the computation of error-locator polynomials as well as a systolic array for combined syndrome computation and polynomial evaluation. With these approaches, the associated optimized architecture improves the latency of computing error-locator polynomials by 47% and the overall decoding latency by 27% compared to a state-of-the-art reference, while requiring only 25% of the area

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