On Dual Lattice Attacks Against Small-Secret LWE and Parameter Choices in HElib and SEAL

We present novel variants of the dual-lattice attack against LWE in the presence of an unusually short secret. These variants are informed by recent progress in BKW-style algorithms for solving LWE. Applying them to parameter sets suggested by the homomorphic encryption libraries HElib and SEAL v2.0 yields revised security estimates. Our techniques scale the exponent of the dual-lattice attack by a factor of $(2\,L)/(2\,L+1)$ when $\log q = \Theta{\left(L \log n\right)}$, when the secret has constant hamming weight $h$ and where $L$ is the maximum depth of supported circuits. They also allow to half the dimension of the lattice under consideration at a multiplicative cost of $2^{h}$ operations. Moreover, our techniques yield revised concrete security estimates. For example, both libraries promise 80 bits of security for LWE instances with $n=1024$ and $\log_2 q \approx {47}$, while the techniques described in this work lead to estimated costs of 68 bits (SEAL v2.0) and 62 bits (HElib)

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

잡음키를 가지는 신원기반 동형암호에 관한 연구

학위논문(박사)--서울대학교 대학원 :자연과학대학 수리과학부,2020. 2. 천정희.클라우드 상의 데이터 분석 위임 시나리오는 동형암호의 가장 효과적인 응용 시나리오 중 하나이다. 그러나, 다양한 데이터 제공자와 분석결과 요구자가 존재하는 실제 현실의 모델에서는 기본적인 암복호화와 동형 연산 외에도 여전히 해결해야 할 과제들이 남아있는 실정이다. 본 학위논문에서는 이러한 모델에서 필요한 여러 요구사항들을 포착하고, 이에 대한 해결방안을 논하였다. 먼저, 기존의 알려진 동형 데이터 분석 솔루션들은 데이터 간의 층위나 수준을 고려하지 못한다는 점에 착안하여, 신원기반 암호와 동형암호를 결합하여 데이터 사이에 접근 권한을 설정하여 해당 데이터 사이의 연산을 허용하는 모델을 생각하였다. 또한 이 모델의 효율적인 동작을 위해서 동형암호 친화적인 신원기반 암호에 대하여 연구하였고, 기존에 알려진 NTRU 기반의 암호를 확장하여 module-NTRU 문제를 정의하고 이를 기반으로 한 신원기반 암호를 제안하였다. 둘째로, 동형암호의 복호화 과정에는 여전히 비밀키가 관여하고 있고, 따라서 비밀키 관리 문제가 남아있다는 점을 포착하였다. 이러한 점에서 생체정보를 활용할 수 있는 복호화 과정을 개발하여 해당 과정을 동형암호 복호화에 적용하였고, 이를 통해 암복호화와 동형 연산의 전 과정을 어느 곳에도 키가 저장되지 않은 상태로 수행할 수 있는 암호시스템을 제안하였다. 마지막으로, 동형암호의 구체적인 안전성 평가 방법을 고려하였다. 이를 위해 동형암호가 기반하고 있는 이른바 Learning With Errors (LWE) 문제의 실제적인 난해성을 면밀히 분석하였고, 그 결과 기존의 공격 알고리즘보다 평균적으로 1000배 이상 빠른 공격 알고리즘들을 개발하였다. 이를 통해 현재 사용하고 있는 동형암호 파라미터가 안전하지 않음을 보였고, 새로운 공격 알고리즘을 통한 파라미터 설정 방법에 대해서 논하였다.Secure data analysis delegation on cloud is one of the most powerful application that homomorphic encryption (HE) can bring. As the technical level of HE arrive at practical regime, this model is also being considered to be a more serious and realistic paradigm. In this regard, this increasing attention requires more versatile and secure model to deal with much complicated real world problems. First, as real world modeling involves a number of data owners and clients, an authorized control to data access is still required even for HE scenario. Second, we note that although homomorphic operation requires no secret key, the decryption requires the secret key. That is, the secret key management concern still remains even for HE. Last, in a rather fundamental view, we thoroughly analyze the concrete hardness of the base problem of HE, so-called Learning With Errors (LWE). In fact, for the sake of efficiency, HE exploits a weaker variant of LWE whose security is believed not fully understood. For the data encryption phase efficiency, we improve the previously suggested NTRU-lattice ID-based encryption by generalizing the NTRU concept into module-NTRU lattice. Moreover, we design a novel method that decrypts the resulting ciphertext with a noisy key. This enables the decryptor to use its own noisy source, in particular biometric, and hence fundamentally solves the key management problem. Finally, by considering further improvement on existing LWE solving algorithms, we propose new algorithms that shows much faster performance. Consequently, we argue that the HE parameter choice should be updated regarding our attacks in order to maintain the currently claimed security level.1 Introduction 1 1.1 Access Control based on Identity 2 1.2 Biometric Key Management 3 1.3 Concrete Security of HE 3 1.4 List of Papers 4 2 Background 6 2.1 Notation 6 2.2 Lattices 7 2.2.1 Lattice Reduction Algorithm 7 2.2.2 BKZ cost model 8 2.2.3 Geometric Series Assumption (GSA) 8 2.2.4 The Nearest Plane Algorithm 9 2.3 Gaussian Measures 9 2.3.1 Kullback-Leibler Divergence 11 2.4 Lattice-based Hard Problems 12 2.4.1 The Learning With Errors Problem 12 2.4.2 NTRU Problem 13 2.5 One-way and Pseudo-random Functions 14 3 ID-based Data Access Control 16 3.1 Module-NTRU Lattices 16 3.1.1 Construction of MNTRU lattice and trapdoor 17 3.1.2 Minimize the Gram-Schmidt norm 22 3.2 IBE-Scheme from Module-NTRU 24 3.2.1 Scheme Construction 24 3.2.2 Security Analysis by Attack Algorithms 29 3.2.3 Parameter Selections 31 3.3 Application to Signature 33 4 Noisy Key Cryptosystem 36 4.1 Reusable Fuzzy Extractors 37 4.2 Local Functions 40 4.2.1 Hardness over Non-uniform Sources 40 4.2.2 Flipping local functions 43 4.2.3 Noise stability of predicate functions: Xor-Maj 44 4.3 From Pseudorandom Local Functions 47 4.3.1 Basic Construction: One-bit Fuzzy Extractor 48 4.3.2 Expansion to multi-bit Fuzzy Extractor 50 4.3.3 Indistinguishable Reusability 52 4.3.4 One-way Reusability 56 4.4 From Local One-way Functions 59 5 Concrete Security of Homomorphic Encryption 63 5.1 Albrecht's Improved Dual Attack 64 5.1.1 Simple Dual Lattice Attack 64 5.1.2 Improved Dual Attack 66 5.2 Meet-in-the-Middle Attack on LWE 69 5.2.1 Noisy Collision Search 70 5.2.2 Noisy Meet-in-the-middle Attack on LWE 74 5.3 The Hybrid-Dual Attack 76 5.3.1 Dimension-error Trade-o of LWE 77 5.3.2 Our Hybrid Attack 79 5.4 The Hybrid-Primal Attack 82 5.4.1 The Primal Attack on LWE 83 5.4.2 The Hybrid Attack for SVP 86 5.4.3 The Hybrid-Primal attack for LWE 93 5.4.4 Complexity Analysis 96 5.5 Bit-security estimation 102 5.5.1 Estimations 104 5.5.2 Application to PKE 105 6 Conclusion 108 Abstract (in Korean) 120Docto

A Hybrid of Dual and Meet-in-the-Middle Attack on Sparse and Ternary Secret LWE

The dual attack is one of the most efficient attack algorithms for the Learning with Errors (LWE) problem. Recently, an efficient variant of the dual attack for sparse and small secret LWE was reported by Albrecht [Eurocrypt 2017], which forces some LWE-based cryptosystems, especially fully homomorphic encryptions (FHE), to change parameters. In this work, we propose a new hybrid of dual and meet-in-the-middle (MITM) attack, which outperforms the improved variant on the same LWE parameter regime. To this end, we adapt the MITM attack for NTRU due to Odlyzko to LWE, and give a rigorous analysis for it. The performance of our MITM attack depends on the relative size of error and modulus, and hence for a large modulus LWE samples, our MITM attack works well for quite large error. We then combine our MITM attack with Albrecht\u27s observation that understands the dual attack as dimension-error tradeoff, which finally yields our hybrid attack. We also implement a sage module that estimates the attack complexity of our algorithm upon {\sf LWE-estimator}, and our attack shows significant performance improvement for the LWE parameter for FHE. For example, for the LWE problem with dimension $n=2^{15}$, modulus $q=2^{628}$ and ternary secret key with Hamming weight 64 which is one parameter set used for {\sf HEAAN} bootstrapping [Eurocrypt 2018], our attack takes $2^{112.5}$ operations and $2^{70.6}$ bit memory while the previous best attack requires $2^{127.2}$ operations as reported by {\sf LWE-estimator}

On the Feasibility and Impact of Standardising Sparse-secret LWE Parameter Sets for Homomorphic Encryption

In November 2018, the HomomorphicEncryption.org consortium published the Homomorphic Encryption Security Standard. The Standard recommends several sets of Learning with Errors (LWE) parameters that can be selected by application developers to achieve a target security level $\lambda \in \{128,192,256\}$. These parameter sets all involve a power-of-two dimension $n \leq 2^{15}$, an error distribution of standard deviation $\sigma \approx 3.19$, and a secret whose coefficients are either chosen uniformly in $Z_q$, chosen according to the error distribution, or chosen uniformly in $\{ -1, 0, 1\}$. These parameter sets do not necessarily reflect implementation choices in the most commonly used homomorphic encryption libraries. For example, several libraries support dimensions that are not a power of two. Moreover, all known implementations for bootstrapping for the CKKS, BFV and BGV schemes use a sparse secret and a large ring dimension such as $n \in \{ 2^{16}, 2^{17} \}$, and advanced applications such as logistic regression have used equally large dimensions. This motivates the community to consider widening the recommended parameter sets, and the purpose of this paper is to investigate such possible extensions. We explore the security of possible sparse-secret LWE parameter sets, taking into account hybrid attacks, which are often the most competitive in the sparse-secret regime. We present a conservative analysis of the hybrid decoding and hybrid dual attacks for parameter sets of varying sparsity, with the goal of balancing security requirements with bootstrapping efficiency. We also show how the methodology in the Standard can be easily adapted to support parameter sets with power-of-two dimension $n \geq 2^{16}$. We conclude with a number of discussion points to motivate future improvements to the Standard

Exploring Trade-offs in Batch Bounded Distance Decoding

Algorithms for solving the Bounded Distance Decoding problem (BDD) are used for estimating the security of lattice-based cryptographic primitives, since these algorithms can be employed to solve variants of the Learning with Errors problem (LWE). In certain parameter regimes where the target vector is small and/or sparse, batches of BDD instances emerge from a combinatorial approach where several components of the target vector are guessed before decoding. In this work we explore trade-offs in solving ``Batch-BDD\u27\u27, and apply our techniques to the small-secret Learning with Errors problem. We compare our techniques to previous works which solve batches of BDD instances, such as the hybrid lattice-reduction and meet-in-the-middle attack. Our results are a mixed bag. We show that, in the ``enumeration setting\u27\u27 and with BKZ reduction, our techniques outperform a variant of the hybrid attack which does not consider time-memory trade-offs in the guessing phase for certain Round5 (17-bits out of 466), Round5-IoT (19-bits out of 240), and NTRU LPrime (23-bits out of 385) parameter sets. On the other hand, our techniques do not outperform the Hybrid Attack under standard, albeit unrealistic, assumptions. Finally, as expected, our techniques do not improve on previous works in the ``sieving setting\u27\u27 (under standard assumptions) where combinatorial attacks in general do not perform well

Hybrid Dual and Meet-LWE Attack

The Learning with Errors (LWE) problem is one of the most prominent problems in lattice-based cryptography. Many practical LWE-based schemes, including Fully Homomorphic encryption (FHE), use sparse ternary secret for the sake of efficiency. Several (hybrid) attacks have been proposed that benefit from such sparseness, thus researchers believe the security of the schemes with sparse ternary secrets is not well-understood yet. Recently, May [Crypto 2021] proposed an efficient meet-in-the-middle attack named Meet-LWE for LWE with ternary se- cret, which significantly improves Odlyzko’s algorithm. In this work, we generalize May’s Meet-LWE and then introduce a new hybrid attack which combines Meet-LWE with lattice dual attack. We implement our algorithm to FHE-type parameters of LWE problem and compare it with the previous hybrid dual attacks. The result shows that our attack outperforms other attacks in a large range of parameters. We note that our attack has no impact on the LWE-based schemes in the PQC Standardization held by NIST as their secrets are not sparse and/or ternary