Approximate Homomorphic Encryption over the Conjugate-invariant Ring

The Ring Learning with Errors (RLWE) problem over a cyclotomic ring has been the most widely used hardness assumption for the construction of practical homomorphic encryption schemes. However, this restricted choice of a base ring may cause a waste in terms of plaintext space usage. For example, an approximate homomorphic encryption scheme of Cheon et al. (ASIACRYPT 2017) is able to store a complex number in each of the plaintext slots since its canonical embedding of a cyclotomic field has a complex image. The imaginary part of a plaintext is not underutilized at all when the computation is performed over the real numbers, which is required in most of the real-world applications such as machine learning. In this paper, we are proposing a new homomorphic encryption scheme which supports arithmetic over the real numbers. Our scheme is based on RLWE over a subring of a cyclotomic ring called conjugate-invariant ring. We show that this problem is no easier than a standard lattice problem over ideal lattices by the reduction of Peikert et al. (STOC 2017). Our scheme allows real numbers to be packed in a ciphertext without any waste of a plaintext space and consequently we can encrypt twice as many plaintext slots as the previous scheme while maintaining the same security level, storage, and computational costs

Optimizing HE operations via Level-aware Key-switching Framework

In lattice-based Homomorphic Encryption (HE) schemes, the key-switching procedure is a core building block of non-linear operations but also a major performance bottleneck. The computational complexity of the operation is primarily determined by the so-called gadget decomposition, which transforms a ciphertext entry into a tuple of small polynomials before being multiplied with the corresponding evaluation key. However, the previous studies such as Halevi et al. (CT-RSA 2019) and Han and Ki (CT-RSA 2020) fix a decomposition function in the setup phase which is applied commonly across all ciphertext levels, resulting in suboptimal performance. In this paper, we introduce a novel key-switching framework for leveled HE schemes. We aim to allow the use of different decomposition functions during the evaluation phase so that the optimal decomposition method can be utilized at each level to achieve the best performance. A naive solution might generate multiple key-switching keys corresponding to all possible decomposition functions, and sends them to an evaluator. However, our solution can achieve the goal without such communication overhead since it allows an evaluator to dynamically derive other key-switching keys from a single key-switching key depending on the choice of gadget decomposition. We implement our framework at a proof-of-concept level to provide concrete benchmark results. Our experiments show that we achieve the optimal performance at every level while maintaining the same computational capability and communication costs

Simpler and Faster BFV Bootstrapping for Arbitrary Plaintext Modulus from CKKS

Bootstrapping is a key operation in fully homomorphic encryption schemes that enables the evaluation of arbitrary multiplicative depth circuits. In the BFV scheme, bootstrapping corresponds to reducing the size of accumulated noise in lower bits while preserving the plaintext in the upper bits. The previous instantiation of BFV bootstrapping is achieved through the digit extraction procedure. However, its performance is highly dependent on the plaintext modulus, so only a limited form of the plaintext modulus, a power of a small prime number, was used for the efficiency of bootstrapping. In this paper, we present a novel approach to instantiate BFV bootstrapping, distinct from the previous digit extraction-based method. The core idea of our bootstrapping is to utilize CKKS bootstrapping as a subroutine, so the performance of our method mainly depends on the underlying CKKS bootstrapping rather than the plaintext modulus. We implement our method at a proof-of-concept level to provide concrete benchmark results. When performing the bootstrapping operation for a 51-bits plaintext modulus, our method improves the previous digit extraction-based method by a factor of 37.9 in latency and 29.4 in throughput. Additionally, we achieve viable bootstrapping performance for large plaintext moduli, such as 144-bits and 234-bits, which has never been measured before

Functional Bootstrapping for FV-style Cryptosystems

Fully Homomorphic Encryption (FHE) enables the computation of an arbitrary function over encrypted data without decrypting them. In particular, bootstrapping is a core building block of FHE which reduces the noise of a ciphertext thereby recovering the computational capability. This paper introduces a new bootstrapping framework for the Fan-Vercauteren (FV) scheme, called the functional bootstrapping, providing more generic and advanced functionality than the ordinary bootstrapping method. More specifically, the functional bootstrapping allows us to evaluate an arbitrary function while removing the error of an input ciphertext. Therefore, we achieve better depth consumption and computational complexity as the evaluation of a circuit can be integrated as part of the functional bootstrapping procedure. In particular, our approach extends the functionality of FV since it is even applicable to functions between different plaintext spaces. At the heart of our functional bootstrapping framework is a homomorphic Look-Up Table (LUT) evaluation method where we represent any LUT using only the operations supported by the FV scheme. Finally, we provide a proof-of-concept implementation and present benchmarks of the functional bootstrapping. In concrete examples, such as delta and sign functions, our functional bootstrapping takes about 46.5s or 171.4s for 9-bit or 13-bit plaintext modulus, respectively

Concretely Efficient Lattice-based Polynomial Commitment from Standard Assumptions

Polynomial commitment is a crucial cryptographic primitive in constructing zkSNARKs. To date, most practical constructions are either insecure against quantum adversaries or lack homomorphic properties, which are useful in recursive compositions of SNARKs. Recently, lattice-based constructions from functional commitments have drawn attention for possessing all the desirable properties, but they yet lack concrete efficiency, and their extractability, which is essential for SNARKs, requires further analysis. In this paper, we propose a novel construction of an extractable polynomial commitment scheme based on standard lattice-based assumptions, which is transparent and publicly verifiable. Our polynomial commitment has a square-root proof size and verification complexity, but it provides concrete efficiency in proof size, proof generation, and verification. When compared with the recent code-based construction based on Brakedown (CRYPTO 23), our construction provides comparable performance in all aspects

Faster TFHE Bootstrapping with Block Binary Keys

Fully Homomorphic Encryption over the Torus (TFHE) is a homomorphic encryption scheme which supports efficient Boolean operations over encrypted bits. TFHE has a unique feature in that the evaluation of each binary gate is followed by a bootstrapping procedure to refresh the noise of a ciphertext. In particular, this gate bootstrapping involves two algorithms called the blind rotation and key-switching. In this work, we introduce several optimization techniques for the TFHE bootstrapping. We first define a new key distribution, called the block binary distribution, where the secret key can be expressed as a concatenation of several vectors of Hamming weight at most one. We analyze the hardness of (Ring) LWE with a block binary secret and provide candidate parameter sets which are secure against the best-known attacks. Then, we use the block key structure to simplify the inner working of blind rotation and reduce its complexity. We also modify the RLWE key generation and the gadget decomposition method to improve the performance of the key-switching algorithm in terms of complexity and noise growth. Finally, we use the TFHE library to implement our algorithms and demonstrate their benchmarks. Our experimentation shows that the execution time of TFHE bootstrapping is reduced from 10.5ms down to 6.4ms under the same security level, and the size of the bootstrapping key decreases from 109MB to 60MB

Multi-Key Homomophic Encryption from TFHE

In this paper, we propose a Multi-Key Homomorphic Encryption (MKHE) scheme by generalizing the low-latency homomorphic encryption by Chillotti et al. (ASIACRYPT 2016). Our scheme can evaluate a binary gate on ciphertexts encrypted under different keys followed by a bootstrapping. The biggest challenge to meeting the goal is to design a multiplication between a bootstrapping key of a single party and a multi-key RLWE ciphertext. We propose two different algorithms for this hybrid product. Our first method improves the ciphertext extension by Mukherjee and Wichs (EUROCRYPT 2016) to provide better performance. The other one is a whole new approach which has advantages in storage, complexity, and noise growth. Compared to previous work, our construction is more efficient in terms of both asymptotic and concrete complexity. The length of ciphertexts and the computational costs of a binary gate grow linearly and quadratically on the number of parties, respectively. We provide experimental results demonstrating the running time of a homomorphic NAND gate with bootstrapping. To the best of our knowledge, this is the first attempt in the literature to implement an MKHE scheme

Towards Practical Multi-key TFHE: Parallelizable, Key-Compatible, Quasi-linear Complexity

Multi-key homomorphic encryption is a generalized notion of homomorphic encryption supporting arbitrary computation on ciphertexts, possibly encrypted under different keys. In this paper, we revisit the work of Chen, Chillotti and Song (ASIACRYPT 2019) and present yet another multi-key variant of the TFHE scheme. The previous construction by Chen et al. involves a blind rotation procedure where the complexity of each iteration gradually increases as it continuously operates on ciphertexts under different keys. Hence, the complexity of gate bootstrapping grows quadratically with respect to the number of associated keys. Our scheme is based on a new blind rotation algorithm which consists of two separate phases. We first split a given multi-key ciphertext into several single-key ciphertexts, take each of them as input to the blind rotation procedure, and obtain accumulators corresponding to individual keys. Then, we merge these single-key accumulators into a single multi-key accumulator. In particular, we develop a novel homomorphic operation between single-key and multi-key ciphertexts to instantiate our pipeline. Therefore, our construction achieves an almost linear time complexity since the gate bootstrapping is dominated by the first phase of blind rotation which requires only independent single-key operations. It also enjoys with great advantages of parallelizability and key-compatibility. We implement the proposed scheme and provide its performance benchmark. For example, our experiment of 16-key gate bootstrapping demonstrates about 4.75x speedup without parallelization, and 55.53x speedup with parallelization over prior work

Toward Practical Lattice-based Proof of Knowledge from Hint-MLWE

In the last decade, zero-knowledge proof of knowledge protocols have been extensively studied to achieve active security of various cryptographic protocols. However, the existing solutions simply seek zero-knowledge for both message and randomness, which is an overkill in many applications since protocols may remain secure even if some information about randomness is leaked to the adversary. We develop this idea to improve the state-of-the-art proof of knowledge protocols for RLWE-based public-key encryption and BDLOP commitment schemes. In a nutshell, we present new proof of knowledge protocols without using noise flooding or rejection sampling which are provably secure under a computational hardness assumption, called Hint-MLWE. We also show an efficient reduction from Hint-MLWE to the standard MLWE assumption. Our approach enjoys the best of two worlds because it has no computational overhead from repetition (abort) and achieves a polynomial overhead between the honest and proven languages. We prove this claim by demonstrating concrete parameters and compare with previous results. Finally, we explain how our idea can be further applied to other proof of knowledge providing advanced functionality