Accelerating LTV based homomorphic encryption in reconfigurable hardware

After being introduced in 2009, the first fully homomorphic encryption (FHE) scheme has created significant excitement in academia and industry. Despite rapid advances in the last 6 years, FHE schemes are still not ready for deployment due to an efficiency bottleneck. Here we introduce a custom hardware accelerator optimized for a class of reconfigurable logic to bring LTV based somewhat homomorphic encryption (SWHE) schemes one step closer to deployment in real-life applications. The accelerator we present is connected via a fast PCIe interface to a CPU platform to provide homomorphic evaluation services to any application that needs to support blinded computations. Specifically we introduce a number theoretical transform based multiplier architecture capable of efficiently handling very large polynomials. When synthesized for the Xilinx Virtex 7 family the presented architecture can compute the product of large polynomials in under 6.25 msec making it the fastest multiplier design of its kind currently available in the literature and is more than 102 times faster than a software implementation. Using this multiplier we can compute a relinearization operation in 526 msec. When used as an accelerator, for instance, to evaluate the AES block cipher, we estimate a per block homomorphic evaluation performance of 442 msec yielding performance gains of 28.5 and 17 times over similar CPU and GPU implementations, respectively

High-Performance VLSI Architectures for Lattice-Based Cryptography

Lattice-based cryptography is a cryptographic primitive built upon the hard problems on point lattices. Cryptosystems relying on lattice-based cryptography have attracted huge attention in the last decade since they have post-quantum-resistant security and the remarkable construction of the algorithm. In particular, homomorphic encryption (HE) and post-quantum cryptography (PQC) are the two main applications of lattice-based cryptography. Meanwhile, the efficient hardware implementations for these advanced cryptography schemes are demanding to achieve a high-performance implementation. This dissertation aims to investigate the novel and high-performance very large-scale integration (VLSI) architectures for lattice-based cryptography, including the HE and PQC schemes. This dissertation first presents different architectures for the number-theoretic transform (NTT)-based polynomial multiplication, one of the crucial parts of the fundamental arithmetic for lattice-based HE and PQC schemes. Then a high-speed modular integer multiplier is proposed, particularly for lattice-based cryptography. In addition, a novel modular polynomial multiplier is presented to exploit the fast finite impulse response (FIR) filter architecture to reduce the computational complexity of the schoolbook modular polynomial multiplication for lattice-based PQC scheme. Afterward, an NTT and Chinese remainder theorem (CRT)-based high-speed modular polynomial multiplier is presented for HE schemes whose moduli are large integers

Fast, compact and secure implementation of rsa on dedicated hardware

RSA is the most popular Public Key Cryptosystem (PKC) and is heavily used today. PKC comes into play, when two parties, who have previously never met, want to create a secure channel between them. The core operation in RSA is modular multiplication, which requires lots of computational power especially when the operands are longer than 1024-bits. Although today’s powerful PC’s can easily handle one RSA operation in a fraction of a second, small devices such as PDA’s, cell phones, smart cards, etc. have limited computational power, thus there is a need for dedicated hardware which is specially designed to meet the demand of this heavy calculation. Additionally, web servers, which thousands of users can access at the same time, need to perform many PKC operations in a very short time and this can create a performance bottleneck. Special algorithms implemented on dedicated hardware can take advantage of true massive parallelism and high utilization of the data path resulting in high efficiency in terms of both power and execution time while keeping the chip cost low. We will use the “Montgomery Modular Multiplication” algorithm in our implementation, which is considered one of the most efficient multiplication schemes, and has many applications in PKC. In the first part of the thesis, our “2048-bit Radix-4 based Modular Multiplier” design is introduced and compared with the conventional radix-2 modular multipliers of previous works. Our implementation for 2048-bit modular multiplication features up to 82% shorter execution time with 33% increase in the area over the conventional radix-2 designs and can achieve 132 MHz on a Xilinx xc2v6000 FPGA. The proposed multiplier has one of the fastest execution times in terms of latency and performs better than (37% better) our reference radix-2 design in terms of time-area product. The results are similar in the ASIC case where we implement our design for UMC 0.18 μm technology. In the second part, a fast, efficient, and parameterized modular multiplier and a secure exponentiation circuit intended for inexpensive FPGAs are presented. The design utilizes hardwired block multipliers as the main functional unit and Block-RAM as storage unit for the operands. The adopted design methodology allows adjusting the number of multipliers, the radix used in the multipliers, and number of words to meet the system requirements such as available resources, precision and timing constraints. The deployed method is based on the Montgomery modular multiplication algorithm and the architecture utilizes a pipelining technique that allows concurrent operation of hardwired multipliers. Our design completes 1020-bit and 2040-bit modular multiplications* in 7.62 μs and 27.0 μs respectively with approximately the same device usage on Xilinx Spartan-3E 500. The multiplier uses a moderate amount of system resources while achieving the best area-time product in literature. 2040-bit modular exponentiation engine easily fits into Xilinx Spartan-3E 500; moreover the exponentiation circuit withstands known side channel attacks with an insignificant overhead in area and execution time. The upper limit on the operand precision is dictated only by the available Block-RAM to accommodate the operands within the FPGA. This design is also compared to the first one, considering the relative advantages and disadvantages of each circuit

A custom accelerator for homomorphic encryption applications

After the introduction of first fully homomorphic encryption scheme in 2009, numerous research work has been published aiming at making fully homomorphic encryption practical for daily use. The first fully functional scheme and a few others that have been introduced has been proven difficult to be utilized in practical applications, due to efficiency reasons. Here, we propose a custom hardware accelerator, which is optimized for a class of reconfigurable logic, for Lopez-Alt, Tromer and Vaikuntanathan’s somewhat homomorphic encryption based schemes. Our design is working as a co-processor which enables the operating system to offload the most compute–heavy operations to this specialized hardware. The core of our design is an efficient hardware implementation of a polynomial multiplier as it is the most compute–heavy operation of our target scheme. The presented architecture can compute the product of very–large polynomials in under 6.25 ms which is 102 times faster than its software implementation. In case of accelerating homomorphic applications; we estimate the per block homomorphic AES as 442 ms which is 28.5 and 17 times faster than the CPU and GPU implementations, respectively. In evaluation of Prince block cipher homomorphically, we estimate the performance as 52 ms which is 66 times faster than the CPU implementation

Reconfigurable Architectures for Cryptographic Systems

Field Programmable Gate Arrays (FPGAs) are suitable platforms for implementing cryptographic algorithms in hardware due to their flexibility, good performance and low power consumption. Computer security is becoming increasingly important and security requirements such as key sizes are quickly evolving. This creates the need for customisable hardware designs for cryptographic operations capable of covering a large design space. In this thesis we explore the four design dimensions relevant to cryptography - speed, area, power consumption and security of the crypto-system - by developing parametric designs for public-key generation and encryption as well as side-channel attack countermeasures. There are four contributions. First, we present new architectures for Montgomery multiplication and exponentiation based on variable pipelining and variable serial replication. Our implementations of these architectures are compared to the best implementations in the literature and the design space is explored in terms of speed and area trade-offs. Second, we generalise our Montgomery multiplier design ideas by developing a parametric model to allow rapid optimisation of a general class of algorithms containing loops with dependencies carried from one iteration to the next. By predicting the throughput and the area of the design, our model facilitates and speeds up design space exploration. Third, we develop new architectures for primality testing including the first hardware architecture for the NIST approved Lucas primality test. We explore the area, speed and power consumption trade-offs by comparing our Lucas architectures on CPU, FPGA and ASIC. Finally, we tackle the security issue by presenting two novel power attack countermeasures based on on-chip power monitoring. Our constant power framework uses a closed-loop control system to keep the power consumption of any FPGA implementation constant. Our attack detection framework uses a network of ring-oscillators to detect the insertion of a shunt resistor-based power measurement circuit on a device's power rail. This countermeasure is lightweight and has a relatively low power overhead compared to existing masking and hiding countermeasures

暗号モジュールへの故障利用攻撃に対する安全性評価手法に関する研究

Tohoku University青木孝

BASALISC: Programmable Hardware Accelerator for BGV Fully Homomorphic Encryption

Fully Homomorphic Encryption (FHE) allows for secure computation on encrypted data. Unfortunately, huge memory size, computational cost and bandwidth requirements limit its practicality. We present BASALISC, an architecture family of hardware accelerators that aims to substantially accelerate FHE computations in the cloud. BASALISC is the first to implement the BGV scheme with fully-packed bootstrapping – the noise removal capability necessary for arbitrary-depth computation. It supports a customized version of bootstrapping that can be instantiated with hardware multipliers optimized for area and power. BASALISC is a three-abstraction-layer RISC architecture, designed for a 1 GHz ASIC implementation and underway toward 150mm2 die tape-out in a 12nm GF process. BASALISC\u27s four-layer memory hierarchy includes a two-dimensional conflict-free inner memory layer that enables 32 Tb/s radix-256 NTT computations without pipeline stalls. Its conflict-resolution permutation hardware is generalized and re-used to compute BGV automorphisms without throughput penalty. BASALISC also has a custom multiply-accumulate unit to accelerate BGV key switching. The BASALISC toolchain comprises a custom compiler and a joint performance and correctness simulator. To evaluate BASALISC, we study its physical realizability, emulate and formally verify its core functional units, and we study its performance on a set of benchmarks. Simulation results show a speedup of more than 5,000× over HElib – a popular software FHE library

Accelerating Homomorphic Evaluation on Reconfigurable Hardware

Homomorphic encryption allows computation on encrypted data and makes it possible to securely outsource computational tasks to untrusted environments. However, all proposed schemes are quite inefficient and homomorphic evaluation of ciphertexts usually takes several seconds on high-end CPUs, even for evaluating simple functions. In this work we investigate the potential of FPGAs for speeding up those evaluation operations. We propose an architecture to accelerate schemes based on the ring learning with errors (RLWE) problem and specifically implemented the somewhat homomorphic encryption scheme YASHE, which was proposed by Bos, Lauter, Loftus, and Naehrig in 2013. Due to the large size of ciphertexts and evaluation keys, on-chip storage of all data is not possible and external memory is required. For efficient utilization of the external memory we propose an efficient double-buffered memory access scheme and a polynomial multiplier based on the number theoretic transform (NTT). For the parameter set (n=16384,log_2(q)=512) capable of evaluating 9 levels of multiplications, we can perform a homomorphic addition in 48.67 and a homomorphic multiplication in 0.94 ms

A Survey on Homomorphic Encryption Schemes: Theory and Implementation

Legacy encryption systems depend on sharing a key (public or private) among the peers involved in exchanging an encrypted message. However, this approach poses privacy concerns. Especially with popular cloud services, the control over the privacy of the sensitive data is lost. Even when the keys are not shared, the encrypted material is shared with a third party that does not necessarily need to access the content. Moreover, untrusted servers, providers, and cloud operators can keep identifying elements of users long after users end the relationship with the services. Indeed, Homomorphic Encryption (HE), a special kind of encryption scheme, can address these concerns as it allows any third party to operate on the encrypted data without decrypting it in advance. Although this extremely useful feature of the HE scheme has been known for over 30 years, the first plausible and achievable Fully Homomorphic Encryption (FHE) scheme, which allows any computable function to perform on the encrypted data, was introduced by Craig Gentry in 2009. Even though this was a major achievement, different implementations so far demonstrated that FHE still needs to be improved significantly to be practical on every platform. First, we present the basics of HE and the details of the well-known Partially Homomorphic Encryption (PHE) and Somewhat Homomorphic Encryption (SWHE), which are important pillars of achieving FHE. Then, the main FHE families, which have become the base for the other follow-up FHE schemes are presented. Furthermore, the implementations and recent improvements in Gentry-type FHE schemes are also surveyed. Finally, further research directions are discussed. This survey is intended to give a clear knowledge and foundation to researchers and practitioners interested in knowing, applying, as well as extending the state of the art HE, PHE, SWHE, and FHE systems.Comment: - Updated. (October 6, 2017) - This paper is an early draft of the survey that is being submitted to ACM CSUR and has been uploaded to arXiv for feedback from stakeholder