What a lovely hat

Functional bootstrapping is a core technique in Fully Homomorphic Encryption(FHE). For large plaintext, to evaluate a general function homomorphically over a ciphertext, in the FHEW/TFHE approach, since the function in look-up table form is encoded in the coefficients of a test polynomial, the degree of the polynomial must be high enough to hold the entire table. This increases the bootstrapping time complexity and memory cost, as the size of bootstrapping keys and keyswitching keys need to...

Privacy-preserving machine learning (PPML) has become increasingly important due to the need to protect sensitive data during training and inference. Secure multiparty computation (MPC) and homomorphic encryption (HE) have emerged as foundational technologies, enabling secure computation over private data. In this work, we provide a systematic comparative overview of MPC frameworks for PPML, focusing on protocols that introduce novel approaches rather than incremental improvements....

Fully homomorphic encryption (FHE) is a powerful and widely used primitive in lots of real-world applications, with IND-CPA as its standard security guarantee. Recently, Li and Micciancio [Eurocrypt'21] introduced IND-CPA-D security, which strengthens the standard IND-CPA security by allowing the attacker to access a decryption oracle for honestly generated ciphertexts (generated via either an encryption oracle or an honest homomorphic circuit evaluation process). Recently, Jung et al....

Approximate Homomorphic Encryption (AHE), introduced by Cheon et al. [CKKS17] offers a powerful solution for encrypting real-valued data by relaxing the correctness requirement and allowing small decryption errors. Existing constructions from (Ring) Learning with Errors achieve standard IND-CPA security, but this does not fully capture scenarios where an adversary observes decrypted outputs. Li and Micciancio [LiMic21] showed that when decryptions are passively leaked, these schemes become...

Secure aggregation enables a central server to compute the sum of client inputs without learning any individual input, even in the presence of dropouts or partial participation. This primitive is fundamental to privacy-preserving applications such as federated learning, where clients collaboratively train models without revealing raw data. We present a new secure aggregation protocol, TACITA, in the single-server setting that satisfies four critical properties simultaneously: (1) one-shot...

Homomorphic attribute-based encryption (HABE) is a useful cryptographic primitive that supports both fine-grained access control and computation over ciphertexts. However, existing HABE schemes are limited to the homomorphic evaluation of circuits with either bounded depth or a restricted number of inputs. To address this problem, we introduce a bootstrappable, fully homomorphic attribute-based encryption (FHABE) scheme that supports computations of circuits with unbounded depth over...

We introduce the rotational-add diffusion layers aimed for applications in the design of arithmetization-oriented (AO) symmetric ciphers, such as fully homomorphic encryption (FHE)-friendly symmetric ciphers. This generalizes the rotational-XOR diffusion layers which have been utilized in the design of many important conventional symmetric ciphers like SHA-256, SM4, ZUC and Ascon. A rotational-add diffusion layer is defined over the finite field $\mathbb{F}_{p}$ for arbitrary prime $p$,...

This paper presents an efficient framework for private Transformer inference that combines Homomorphic Encryption (HE) and Secure Multi-party Computation (MPC) to protect data privacy. Existing methods often leverage HE for linear layers (e.g., matrix multiplications) and MPC for non-linear layers (e.g., Softmax activation functions), but the conversion between HE and MPC introduces significant communication costs. The proposed framework, dubbed BLB, overcomes this by breaking down layers...

Homomorphic encryption (HE) is a promising technique for privacy-preserving data analysis. Several HE schemes have been developed, with the CKKS and TFHE schemes being two of the most advanced. However, due to their differences, it is hard to compare their performance and suitability for a given application. We therefore conducted an empirical study of the performance of the two schemes in a comparable scenario. We benchmarked the commonly used operations addition, multiplication, division,...

This paper addresses the challenge of best arm identification in stochastic multi-armed bandit (MAB) models under privacy-preserving constraints, such as in dynamic spectrum access networks where secondary users must privately detect underutilized channels. While previous network security research has explored securing MAB algorithms through techniques such as homomorphic encryption or differential privacy, these methods often suffer from high computational overhead or introduce noise that...

Encrypted matrix-vector multiplication is a fundamental component of a variety of applications that involve data privacy concerns. Current algorithms utilizing fully homomorphic encryption (FHE) generally use batching to enhance computational efficiency while neglecting the sparsity of the matrices, a characteristic that exists naturally in many practical situations. Alternatively, porting plaintext algorithms that address sparsity may fail to utilize batching and introduce additional...

CKKS bootstrapping requires a significant computational overhead and modulus consumption. In this work, we improve the homomorphic linear transformation algorithm with lower time complexity and less modulus consumption. We first propose a novel rescaling operation, called level-conserving rescaling, that acts on CoeffsToSlots for saving moduli. Secondly, we reconstruct the rotation keys and merge the plaintext-ciphertext multiplication and rescaling operations into the key-switching...

Optimizing Boolean circuits presents a considerable challenge, especially when aiming to construct circuits amenable to Fully Homomorphic Encryption (FHE) schemes. FHE enables arbitrary computations on encrypted data but incorporates a computationally intensive operation called bootstrapping, necessary for reducing noise in ciphertexts to facilitate computations on circuits of arbitrary depth. This operation can consume a substantial amount of time, depending on the size of the circuits. To...

Fully homomorphic encryption (FHE) enables computations over encrypted data without the need for decryption. Recently there has been an increased interest in developing FHE based algorithms to facilitate encrypted matrix multiplication (EMM) due to rising data security concerns surrounding cyber-physical systems, sensor processing, blockchain, and machine learning. Presently, FHE operations have a high computational overhead, resulting in an increased need for low operational complexity...

We present InsPIRe that is the first private information retrieval (PIR) construction simultaneously obtaining both high-throughput and low query communication while using silent preprocessing (meaning no offline communication). Prior PIR schemes with both high-throughput and low query communication required substantial offline communication of either downloading a database hint that is 10-100x larger than the communication cost of a single query (such as SimplePIR and DoublePIR [Henzinger...

Fully Homomorphic Encryption (FHE) is an encryption scheme that allows for computation to be performed directly on encrypted data. FHE effectively closes the loop on secure and outsourced computing; data is encrypted not only during rest and transit, but also during processing. Moreover, modern FHE schemes such as RNS-CKKS (with the canonical slot encoding) encrypt one-dimensional floating-point vectors, which makes such a scheme an ideal candidate for building private machine learning...

The (Multi-)Scalar multiplication is a crucial operation during FHE-related AI applications, and its performance has a significant impact on the overall efficiency of these applications. In this paper we introduce SMOOTHIE: (Multi-)Scalar Multiplication Optimizations On TFHE, introducing new techniques to improve the performance of single- and multi-scalar multiplications in TFHE. We show that by taking the bucket method, known from the Elliptic Curve field, significant improvements can be...

Modern efficient secure multi-party computation (MPC) protocols typically follow an offline-online design, where offline protocols produce a sufficient amount of correlated randomness that would be consumed during the online phases. The past decades have witnessed maturing of efficient online protocols, for computing circuits over either arbitrary finite fields or rings $\mathbb{Z}_{p^k}$. In particular, protocols tailored for $\mathbb{Z}_{2^k}$ arithmetic have achieved better concrete...

Homomorphic encryption (HE) schemes have gained significant popularity in modern privacy-preserving applications across various domains. While research on HE constructions based on learning with errors (LWE) and ring-LWE has received major attention from both cryptographers and software-hardware designers alike, their module-LWE-based counterpart has remained comparatively under-explored in the literature. A recent work provides a module-LWE-based instantiation (MLWE-HE) of the...

Sorting encrypted values is an open research problem that plays a crucial role in the broader objective of providing efficient and practical privacy-preserving online services. The current state of the art work by Mazzone, Everts, Hahn and Peter (USENIX Security '25) proposes efficient algorithms for ranking, indexing and sorting based on the CKKS scheme, which deviates from the compare-and-swap paradigm, typically used by sorting networks, using a permutation-based approach. This allows...

Private set intersection (PSI) allows two participants to compute the intersection of their private sets without revealing any additional information beyond the intersection itself. It is known that oblivious linear evaluation (OLE) can be used to construct the online efficient PSI protocol (Kerschbaum \textit{et al.}, NDSS'23). However, oblivious transfer (OT) and fully homomorphic encryption (FHE)-based offline OLE generation are expensive, and the online computational complexity is...

The advent of Large Language Models (LLM) has brought about a new wave productivity, revolutionizing business operations while keeping cost relatively low. The human-like interface of LLM enables it to be easily integrated with business functions, thereby freeing up precious human resources for more complex, valuable tasks. However, due to the intensive computation and memory requirements of LLM inference, it is preferable and cheaper to deploy LLMs with the Cloud Service Providers (CSP)...

Some of the most valuable applications of homomorphic encryption, such as encrypted machine learning inference, require efficient large-scale plaintext-ciphertext and ciphertext-ciphertext matrix multiplications. Current state-of-the-art techniques for matrix multiplications all build on the ability to pack many ciphertexts into a ciphertext and compute on them in a Single Instruction, Multiple Data (SIMD) manner. However, to fit the operation of matrix multiplication into this computational...

Following Gentry's seminal work (STOC 2009), Fully Homomorphic Encryption (FHE) has made significant advancements and can even evaluate functions in the bootstrapping process, called functional bootstrapping. Recently, Liu and Wang (ASIACRYPT 2023) proposed a new approach to functional bootstrapping, which bootstrapped ciphertexts in 7ms amortized time. Their methods packed the secret key of the TFHE cryptosystem into a ciphertext of the BFV cryptosystem, followed by performing functional...

Private set intersection (PSI) is a well-researched cryptographic primitive that allows two parties to compute the intersection of their input sets without revealing any information about items outside of the intersection. Fuzzy private set intersection is a relatively new variant of PSI, where items are not matched exactly but ``fuzzily''. Most commonly, items are points $\mathbf{q},\mathbf{w}$ in $d$-dimensional integer space $\mathbb{Z}^d$ and a point is a fuzzy match to another if it...

Threshold signatures, especially ECDSA, enhance key protection by addressing the single-point-of-failure issue. Threshold signing can be divided into offline and online phases, based on whether the message is required. Schemes with low-cost online phases are referred to as ``online-friendly". Another critical aspect of threshold ECDSA for real-world applications is robustness, which guarantees the successful completion of each signing execution whenever a threshold number $t$ of semi-honest...

The Generalized BFV [Geelen and Vercauteren; Eurocrypt'25] is an efficient fully homomorphic encryption scheme that supports integer computations over large cyclotomic moduli. However, the only known bootstrapping approach cannot support large precision as it uses BFV linear transformation as a subroutine. In this work, we introduce a GBFV bootstrapping that relies on CKKS bootstrapping as in the BFV bootstrapping from CKKS [Kim et al.; CCS'24]. The new bootstrapping can handle arbitrary...

We introduce PaCo, a novel and efficient bootstrapping procedure for the CKKS homomorphic encryption scheme, where PaCo stands for “(Bootstrapping via) Partial CoeffToSlot”. At a high level, PaCo reformulates the CKKS decryption equation in terms of blind rotations and modular additions. This reformulated decryption circuit is then evaluated homomorphically within the CKKS framework. Our approach makes use of the circle group in the complex plane to simulate modular additions via complex...

Private set intersection (PSI) enables a sender holding a set $Q$ and a receiver holding a set $W$ to securely compute the intersection $Q\cap W$. Fuzzy PSI (FPSI) is a PSI variant where the receiver learns the items $q\in Q$ for which there exists $w\in W$ such that $\dist(q, w) \leq \delta$ with respect to some distance metric. Recently, Gao et al. (ASIACRYPT 2024) proposed the first FPSI protocols for $L_\infty$ and $L_{p\in[1,\infty)}$ distance with linear complexity. They summarized...

Homomorphic encryption is a powerful tool that enables computation on encrypted data without requiring decryption. While many Fully Homomorphic Encryption schemes, supporting arbitrary computations on encrypted data, have been developed using lattice-based and AGCD-based approaches, progress in composite groups has been limited to Partial Homomorphic Encryption schemes, which only support either addition or multiplication. This paper introduces the first $\ell$-leveled homomorphic encryption...

Homomorphic Encryption (HE) is a fundamental Privacy-Enhancing Technology (PET) that enables computations on encrypted data without decryption. Despite its utility, designing an efficient and secure HE scheme is highly complex, requiring sophisticated cryptographic techniques. This paper introduces a novel approach to achieving homomorphic properties—supporting either one addition or one multiplication—within composite groups. While the proposed technique exhibits one-wayness, it has a good...

Implementations of modern FHE schemes are available in various highly-optimized libraries. Many of these libraries are designed to allow developers who may not have deep expertise in FHE to build fast and secure privacy-preserving applications. To support such users, the API of these libraries often hides the internals of the schemes in question from the user. However, this design choice makes it hard for users of these libraries to modify existing schemes, or implement new ones; work that...

In key-and-message homomorphic encryption (KMHE), the key space is a subset of the message space, allowing encryption of secret keys such that the same homomorphism can be applied to both the key and the message of a given ciphertext. KMHE with suitable security properties is the main building block for constructing rerandomizable garbling schemes (RGS, Gentry et al., CRYPTO 2010), which enable advanced cryptographic applications like multi-hop homomorphic encryption, the YOSO-like MPC...

SPDZ-style and BMR-style protocols are widely known as practical MPC protocols that achieve active security in the dishonest majority setting. However, to date, SPDZ-style protocols have not achieved constant rounds, and BMR-style protocols have struggled to achieve scalable communication or computation. Additionally, there exists fully homomorphic encryption (FHE)-based MPC protocols that achieve both constant rounds and scalable communication, but they face challenges in achieving active...

Private information retrieval (PIR) enables a client to retrieve data from a server while preserving the confidentiality of the client's query. When PIR is instantiated with fully homomorphic encryption (FHE), the protocol becomes non-interactive, requiring only a query-answer exchange, and it achieves asymptotically optimal communication and computation complexity. Although several FHE-based PIR protocols have been practically implemented with the desired properties, there has been little...

Fully Homomorphic Encryption (FHE) presents unique challenges in programming due to the contrast between traditional and FHE language paradigms. A key challenge is selecting ciphertext configurations (CCs) to achieve the desired level of security, performance, and accuracy simultaneously. Finding the design point satisfying the goal is often labor-intensive (probably impossible), for which reason previous works settle down to a reasonable CC that brings acceptable performance. When FHE is...

A Threshold Fully Homomorphic Encryption (ThFHE) scheme enables the generation of a global public key and secret key shares for multiple parties, allowing any threshold of these parties to collaboratively decrypt a ciphertext without revealing their individual secret keys. By leveraging the homomorphic properties of FHE, this scheme supports the distributed computation of arbitrary functions across multiple parties. As distributed execution of cryptographic tasks becomes popular, the...

Plaintext-ciphertext matrix multiplication (PC-MM) is an indispensable tool in privacy-preserving computations such as secure machine learning and encrypted signal processing. While there are many established algorithms for plaintext-plaintext matrix multiplication, efficiently computing plaintext-ciphertext (and ciphertext-ciphertext) matrix multiplication is an active area of research which has received a lot of attention. Recent literature have explored various techniques for...

Federated Learning (FL) allows clients to engage in learning without revealing their raw data. However, traditional FL focuses on developing a single global model for all clients, limiting their ability to have personalized models tailored to their specific needs. Personalized FL (PFL) enables clients to obtain their customized models, either with or without a central party. Current PFL research includes mechanisms to detect poisoning attacks, in which a couple of malicious nodes try to...

The major Fully Homomorphic Encryption (FHE) schemes guarantee the privacy of the encrypted message only in the honest-but-curious setting, when the server follows the protocol without deviating. However, various attacks in the literature show that an actively malicious server can recover sensitive information by executing incorrect functions, tampering with ciphertexts, or observing the client’s reaction during decryption. Existing integrity solutions for FHE schemes either fail to...

Fully Homomorphic Encryption (FHE) enables computation on encrypted data without decryption, demonstrating significant potential for privacy-preserving applications. However, FHE faces several challenges, one of which is the significant plaintext-to-ciphertext expansion ratio, resulting in high communication overhead between client and server. The transciphering technique can effectively address this problem by first encrypting data with a space-efficient symmetric cipher, then converting...

We introduce Sparse Roots of Unity (SPRU) bootstrapping, a new bootstrapping algorithm for the CKKS homomorphic encryption scheme for approximate arithmetic. The original CKKS bootstrapping method relies on homomorphically evaluating a polynomial that approximates modular reduction modulo q. In contrast, SPRU bootstrapping directly embeds the additive group modulo q into the complex roots of unity, which can be evaluated natively in the CKKS scheme. This approach significantly reduces the...

Homomorphic Encryption (HE) is a cryptographic primitive that enables computation on encrypted data while preserving user privacy. We explore its application in the multi-party setting, where data is stored in the cloud encrypted under several distinct keys. A straightforward approach is to use Multi-Key Homomorphic Encryption (MKHE), which supports computation over ciphertexts encrypted under different keys. However, MKHE incurs space and computational overhead of $O(n)$ with respect to...

Recently, Differential Fault Attacks (DFAs) have proven highly effective against stream ciphers designed for Hybrid Homomorphic Encryption (HHE). In this work, we present a table-based DFA framework called the \textit{shortcut attack}, which generalizes the attack proposed by Wang and Tang on the cipher \textsf{Elisabeth}. The framework applies to a broad sub-family of ciphers following the Group Filter Permutator (GFP) paradigm and enhances previous DFAs by improving both the fault...

Bootstrapping in approximate homomorphic encryption involves evaluating the modular reduction function. Traditional methods decompose the modular reduction function into three components: scaled cosine, double-angle formula, and inverse sine. While these approaches offer a strong trade-off between computational cost and level consumption, they lack flexibility in parameterization. In this work, we propose a new method to decompose the modular reduction function with improved...

A tuple of NP statements $(x_1, \ldots, x_k)$ satisfies a monotone policy $P \colon \{0,1\}^k \to \{0,1\}$ if $P(b_1,\ldots,b_k)=1$, where $b_i = 1$ if and only if $x_i$ is in the NP language. A monotone-policy batch argument (monotone-policy BARG) for NP is a natural extension of regular batch arguments (BARGs) that allows a prover to prove that $x_1, \ldots, x_k$ satisfy a monotone policy $P$ with a proof of size $\mathsf{poly}(\lambda, |\mathcal{R}|, \log k)$, where $|\mathcal{R}|$ is the...

Lee et al. proposed a new bootstrapping algorithm based on homomorphic automorphism, which merges the empty sets of ciphertexts by adjusting the window size. This algorithm supports arbitrary secret key distributions with no additional runtime costs while using small evaluation keys. However, our implementation reveals that once the window size exceeds a certain threshold, the time required for bootstrapping remains relatively constant. This observation prompts the question of how to further...

Oblivious Transfer (OT) is a fundamental cryptographic primitive introduced nearly four decades ago. OT allows a receiver to select and learn $t$ out of $n$ private messages held by a sender. It ensures that the sender does not learn which specific messages the receiver has chosen, while the receiver gains no information about the remaining $n − t$ messages. In this work, we introduce the notion of functional OT (FOT), for the first time. FOT adds a layer of security to the conventional OT...

There has been remarkable progress in fully homomorphic encryption, ever since Gentry's first scheme. In contrast, fully homomorphic authentication primitives received relatively less attention, despite existence of some previous constructions. While there exist various schemes with different functionalities for fully homomorphic encryption, there are only a few options for fully homomorphic authentication. Moreover, there are even fewer options when considering two of the most important...

There is a heavy preference towards instantiating BGV and BFV homomorphic encryption schemes where the cyclotomic order $m$ is a power of two, as this admits highly efficient fast Fourier transformations. Field Instruction Multiple Data (FIMD) was introduced to increase packing capacity in the case of small primes and improve amortised performance, using reverse multiplication-friendly embeddings (RMFEs) to encode more data into each SIMD slot. However, FIMD currently does not admit...

As introduced by Persiano {\it et al.} (Eurocrypt'22), anamorphic encryption (AE) is a primitive enabling private communications against a dictator that forces users to surrender their decryption keys. In its fully asymmetric flavor (defined by Catalano {\it et al.}, Eurocrypt'24), anamorphic channels can work as hidden public-key mechanisms in the sense that anamorphic encryptors are not necessarily able to decrypt anamorphic ciphertexts. Unfortunately, fully asymmetric AE is hard to come...

Threshold signatures have become a critical tool in cryptocurrency systems, offering enhanced security by distributing the signing process among multiple signers. In this work, we distribute this process between a client and a permissionless decentralized blockchain, and present novel protocols for ECDSA and EdDSA/Schnorr signatures in this setting. Typical threshold access architectures used by trusted custodians suffer from the honeypot problem, wherein the more assets the custodian holds,...

We show that the randomized TFHE bootstrapping technique of Bourse and Izabechéne provides a form of sanitization which is error-simulatable. This means that the randomized bootstrap can be used not only for sanitization of ciphertexts (i.e. to hide the function that has been computed), but that it can also be used in server-assisted threshold decryption. Thus we extend the server-assisted threshold decryption method of Passelégue and Stehlé (ASIACRYPT '24) to FHE schemes which have small...

Garbling schemes are a fundamental cryptographic tool for enabling private computations and ensuring that nothing leaks beyond the output. As a widely studied primitive, significant efforts have been made to reduce their size. Until recently, all such schemes followed the Lindell and Pinkas paradigm for Boolean circuits (JoC 2009), where each gate is represented as a set of ciphertexts computed using only symmetric-key primitives. However, this approach is inherently limited to 𝑂(𝜆) bits per...

Software watermarking for cryptographic functionalities enables embedding an arbitrary message (a mark) into a cryptographic function. An extraction algorithm, when provided with a (potentially unauthorized) circuit, retrieves either the embedded mark or a special symbol unmarked indicating the absence of a mark. It is difficult to modify or remove the embedded mark without destroying the functionality of a marked function. Previous works have primarily employed black-box extraction...

Publicly identifiable abort is a critical feature for ensuring accountability in outsourced computations using secure multiparty computation (MPC). Despite its importance, no prior work has specifically addressed identifiable abort in the context of outsourced computations. In this paper, we present the first MPC protocol that supports publicly identifiable abort with minimal overhead for external clients. Our approach minimizes client-side computation by requiring only a few pseudorandom...

Floating-point arithmetic plays a central role in computer science and is used in various domains where precision and computational scale are essential. One notable application is in machine learning, where Fully Homomorphic Encryption (FHE) can play a crucial role in safeguarding user privacy. In this paper, we focus on TFHE and develop novel homomorphic operators designed to enable the construction of precise and adaptable homomorphic floating-point operations. Integrating floating-point...

We study the round-complexity of secure multi-party computation (MPC) in the post-quantum regime where honest parties and communication channels are classical but the adversary can be a quantum machine. Our focus is on the $\mathit{fully}$ black-box setting where both the construction as well as the security reduction are black-box in nature. In this context, Chia, Chung, Liu, and Yamakawa [FOCS'22] demonstrated the infeasibility of achieving standard simulation-based security within...

We introduce a general template for building garbled circuits with low communication, under the decisional composite residuosity (DCR) assumption. For the case of layered Boolean circuits, we can garble a circuit of size $s$ with communication proportional to $O(s/\log\log s)$ bits, plus an additive factor that is polynomial in the security parameter. For layered arithmetic circuits with $B$-bounded integer computation, we obtain a similar result: the garbled arithmetic circuit has size...

A privately constrained pseudorandom function (pCPRF) is a PRF with the additional property that one can derive a constrained key that allows evaluating the PRF only on inputs satisfying a constraint predicate $C$, without revealing $C$ itself or leaking information about the PRF’s output on inputs that do not satisfy the constraint. Existing privately constrained PRFs face significant limitations: either (1) they rely on assumptions known to imply fully-homomorphic encryption or...

Fully homomorphic encryption (FHE) enables the computation of arbitrary circuits over encrypted data. A widespread application of FHE is a simple two-party computation (2PC) protocol, where the server evaluates a circuit over the client's encrypted data and its private inputs. However, while the security of FHE guarantees that the client's data is protected from the server, there is no inherent support for the privacy of the server's input and the circuit. One effective solution to this...

The GINX method in TFHE enables low-latency ciphertext bootstrapping with relatively small bootstrapping keys but is limited to binary or ternary key distributions. In contrast, the AP method supports arbitrary key distributions, albeit at the cost of significantly large bootstrapping keys. Building on AP, automorphism-based methods, introduced in LMK⁺ (EUROCRYPT 2023), achieve smaller key sizes. However, each automorphism application necessitates a key switch, introducing additional...

This paper presents a novel approach to verifiable vote tallying using additive homomorphism, which can be appended to existing voting systems without modifying the underlying infrastructure. Existing End-to-End Verifiable (E2E-V) systems like Belenios and ElectionGuard rely on distributed trust models or are vulnerable to decryption compromises, making them less suitable for general elections. Our approach introduces a tamper-evident commitment to votes through cryptographic hashes...

We present the first complete adaptively secure asynchronous MPC protocol for the YOSO (You Speak Only Once) setting. In contrast to many previous MPC constructions in the YOSO model, we provide a full stack implementation that does MPC, role assignment and total order broadcast. Therefore, our construction is also the first to provide adaptively secure asynchronous total order broadcast and MPC that is sub-quadratic in the number of parties and does not require threshold fully homomorphic...

In this work, we report on the latest GPU implementations of the three well-known methods for the key switching operation, which is critical for Fully Homomorphic Encryption (FHE). Additionally, for the first time in the literature, we provide implementations of all three methods in GPU for leveled CKKS schemes. To ensure a fair comparison, we employ the most recent GPU implementation of the number-theoretic transform (NTT), which is the most time-consuming operation in key switching, and...

Quantum key leasing, also known as public key encryption with secure key leasing (PKE-SKL), allows a user to lease a (quantum) secret key to a server for decryption purpose, with the capability of revoking the key afterwards. In the pioneering work by Chardouvelis et al (arXiv:2310.14328), a PKE-SKL scheme utilizing classical channels was successfully built upon the noisy trapdoor claw-free (NTCF) family. This approach, however, relies on the superpolynomial hardness of learning with...

We put forth and instantiate a new primitive we call simultaneous-message and succinct (SMS) secure computation. An SMS scheme enables a minimal communication pattern for secure computation in the following scenario: Alice has a large private input X, Bob has a small private input y, and Charlie wants to learn $f(X, y)$ for some public function $f$. Given a common reference string (CRS) setup phase, an SMS scheme for a function f is instantiated with two parties holding inputs $X$ and...

Distributed Point Functions (DPFs) are a useful cryptographic primitive enabling a dealer to distribute short keys to two parties, such that the keys encode additive secret shares of a secret point function. However, in many applications of DPFs, no single dealer entity has full knowledge of the secret point function, necessitating the parties to run an interactive protocol to emulate the setup. Prior works have aimed to minimize complexity metrics of such distributed setup protocols, e.g.,...

The CKKS scheme is traditionally recognized for approximate homomorphic encryption of real numbers, but BLEACH (Drucker et al., JoC 2024) extends its capabilities to handle exact computations on binary or small integer numbers. Despite this advancement, BLEACH's approach of simulating XOR gates via $(a-b)^2$ incurs one multiplication per gate, which is computationally expensive in homomorphic encryption. To this end, we introduce XBOOT, a new framework built upon BLEACH's blueprint but...

In various real-world situations, a client may need to verify whether specific data elements they possess are part of a set segmented among numerous data holders. To maintain user privacy, it’s essential that both the client’s data elements and the data holders’ sets remain encrypted throughout the process. Existing approaches like Private Set Intersection (PSI), Multi-Party PSI (MPSI), Private Segmented Membership Test (PSMT), and Oblivious RAM (ORAM) face challenges in these...

Hybrid Homomorphic Encryption (HHE) is considered a promising solution for key challenges that emerge when adopting Homomorphic Encryption (HE). In cases such as communication and computation overhead for clients and storage overhead for servers, it combines symmetric cryptography with HE schemes. However, despite a decade of advancements, enhancing HHE usability, performance, and security for practical applications remains a significant stake. This work contributes to the field by...

Fuzzy private set intersection (Fuzzy PSI) is a cryptographic protocol for privacy-preserving similarity matching, which is one of the essential operations in various real-world applications such as facial authentication, information retrieval, or recommendation systems. Despite recent advancements in fuzzy PSI protocols, still a huge barrier remains in deploying them for these applications. The main obstacle is the high dimensionality, e.g., from 128 to 512, of data; lots of existing...

This paper presents a novel approach to calculating the Levenshtein (edit) distance within the framework of Fully Homomorphic Encryption (FHE), specifically targeting third-generation schemes like TFHE. Edit distance computations are essential in applications across finance and genomics, such as DNA sequence alignment. We introduce an optimised algorithm that significantly reduces the cost of edit distance calculations called Leuvenshtein. This algorithm specifically reduces the number of...

Multi-party Private Set Union (MPSU) enables multiple participants to jointly compute the union of their private sets without leaking any additional information beyond the resulting union. Liu et al. (ASIACRYPT 2023) proposed the first scalable MPSU protocol fully based on symmetric key encryption (SKE), which designates one participant as the "leader" responsible for obtaining the final union. However, the protocol assumes that the leader does not collude with other participants, which...

Emerging cryptographic systems such as Fully Homomorphic Encryption (FHE) and Zero-Knowledge Proofs (ZKP) are computation- and data-intensive. FHE and ZKP implementations in software and hardware largely rely on the von Neumann architecture, where a significant amount of energy is lost on data movements. A promising computing paradigm is computing in memory (CIM), which enables computations to occur directly within memory, thereby reducing data movements and energy consumption. However,...

We present BitGC, a garbling scheme for Boolean circuits with 1 bit per gate communication based on either ring learning with errors (RLWE) or NTRU assumption, with key-dependent message security. The garbling consists of 1) a homomorphically encrypted seed that can be expanded to encryption of many pseudo-random bits and 2) one-bit stitching information per gate to reconstruct garbled tables from the expanded ciphertexts. By using low-complexity PRGs, both the garbling and evaluation of...

This work investigates constructions of threshold fully homomorphic encryption with low communication, i.e., with small ciphertexts and small decryption shares. In this context, we discuss in detail the technicalities for achieving full-fledged threshold FHE, and put forward limitations regarding prior works, including an attack against the recent construction of Boudgoust and Scholl [ASIACRYPT 2023]. In light of our observations, we generalize the definition of threshold fully homomorphic...

The proliferation of data outsourcing and cloud services has heightened privacy vulnerabilities. CKKS, among the most prominent homomorphic encryption schemes, allows computations on encrypted data, serving as a critical privacy safeguard. However, performance remains a central bottleneck, hindering widespread adoption. Existing optimization efforts often prioritize latency reduction over throughput performance. This paper presents HI-CKKS, a throughput-oriented High-performance...

Private Set Intersection (PSI) is a cryptographic primitive that allows two parties to obtain the intersection of their private input sets while revealing nothing more than the intersection. PSI and its numerous variants, which compute on the intersection of items and their associated weights, have been widely studied. In this paper, we revisit the problem of finding the best item in the intersection according to weight sum introduced by Beauregard et al. (SCN '22), which is a special...

This paper focuses on the issue of reducing the bandwidth requirement for FHE ciphertext transmission. While this issue has been extensively studied from the uplink viewpoint (transmission of encrypted inputs towards a FHE calculation), where several approaches exist to essentially cancel FHE ciphertext expansion, the downlink case (transmission of encrypted results towards an end-user) has been the object of much less attention. In this paper, we address this latter issue with a particular...

Fully Homomorphic Encryption (FHE) enables privacy-preserving computation but imposes significant computational and communication overhead on the client for the public-key encryption. To alleviate this burden, previous works have introduced the Hybrid Homomorphic Encryption (HHE) paradigm, which combines symmetric encryption with homomorphic decryption to enhance performance for the FHE client. While early HHE schemes focused on binary data, modern versions now support integer prime fields,...

Private information retrieval (PIR) is a key component of many privacy-preserving systems. Although numerous PIR protocols have been proposed, designing a PIR scheme with communication overhead independent of the database size $N$ and computational cost practical for real-world applications remains a challenge. In this paper, we propose the NewtonPIR protocol, a communication efficient single-server PIR scheme. NewtonPIR can directly generate query values for the entire index without...

The field of Fully Homomorphic Encryption (FHE) has seen many theoretical and computational advances in recent years, bringing the technology closer to practicality than ever before. For this reason, practitioners in related fields, such as machine learning, are increasingly interested in using FHE to provide privacy to their applications. Despite this progress, selecting secure and efficient parameters for FHE remains a complex and challenging task due to the intricate interdependencies...

FHE enables computations on encrypted data, proving itself to be an essential building block for privacy-preserving applications. However, it involves computationally demanding operations such as polynomial multiplication, with the NTT being the state-of-the-art solution to perform it. Considering that most FHE schemes operate over the negacyclic ring of polynomials, we introduce a novel formulation of the hierarchical Four-Step NTT approach for the negacyclic ring, eliminating the need for...

Homomorphic encryption (HE) is a foundational technology in privacy-enhancing cryptography, enabling computation over encrypted data. Recently, generalized HE primitives designed for multi-party applications, such as multi-party HE (MPHE), have garnered significant research interest. While constructing secure multi-party protocols from MPHE in the semi-honest model is straightforward, achieving malicious security remains challenging as it requires zero-knowledge arguments of knowledge...

Boneh et al. (CRYPTO'18) proposed two $t$-out-of-$N$ threshold fully homomorphic encryption ($\sf TFHE$) schemes based on Shamir secret sharing scheme and $\{0,1\}$-linear secret sharing scheme. They demonstrated the simulation security, ensuring no information leakage during partial or final decryption. This breakthrough allows any scheme to be converted into a threshold scheme by using $\sf TFHE$. We propose two polynomial time algorithms to break the simulation security of...

We construct fully-homomorphic NIZKs from a broader range of cryptographic assumptions, including LWE, $O(1)$-LIN, and DDH (without circular security assumptions). Prior to this work, homomorphic NIZKs were only known based on pairing-based techniques. A key ingredient that we develop in this work is a new notion of a partially-hiding succinct delegation system, that we call encrypted RAM (eRAM) delegation. In addition to homomorphic NIZKs, we show that eRAM delegation is also useful for...

We construct somewhat homomorphic encryption from the sparse learning-parities-with-noise problem, along with any assumption that implies linearly homomorphic encryption (e.g., the decisional Diffie-Hellman or decisional composite residuosity assumptions). Our resulting schemes support an a-priori bounded number of homomorphic operations: $O(\log \lambda / \log \log \lambda)$ multiplications followed by poly($\lambda$) additions, where $\lambda$ is a security parameter. These schemes have...

Homomorphic Encryption (HE) technology allows for processing encrypted data, breaking through data isolation barriers and providing a promising solution for privacy-preserving computation. The integration of HE technology into Convolutional Neural Network (CNN) inference shows potential in addressing privacy issues in identity verification, medical imaging diagnosis, and various other applications. The CKKS HE algorithm stands out as a popular option for homomorphic CNN inference due to its...

This paper explores advancements in the Gentry-Sahai-Waters (GSW) fully homomorphic encryption scheme, addressing challenges related to message data range limitations and ciphertext size constraints. We introduce a novel approach utilizing the Chinese Remainder Theorem (CRT) for message decomposition, significantly expanding the allowable message range to the entire plaintext space. This method enables unrestricted message selection and supports parallel homomorphic operations without...

Non-interactive zero-knowledge proofs (NIZK) are essential building blocks in threshold cryptosystems like multiparty signatures, distributed key generation, and verifiable secret sharing, allowing parties to prove correct behavior without revealing secrets. Furthermore, universally composable (UC) NIZKs enable seamless composition in the larger cryptosystems. A popular way to construct NIZKs is to compile interactive protocols using the Fiat-Shamir transform. Unfortunately, Fiat-Shamir...

Transciphering (or Hybrid-Homomorphic Encryption, HHE) is an es- tablished technique for avoiding ciphertext expansion in HE applications, saving communication and storage resources. Recently, it has also been shown to be a fundamental component in the practical construction of HE-based multi-party computation (MPC) protocols, being used both for input data and intermediary results (Smart, IMACC 2023). In these protocols, however, ciphers are used with keys that are jointly generated by...

In aggregation queries, predicate parameters often reveal user intent. Protecting these parameters is critical for user privacy, regardless of whether the database is public or private. While most existing works focus on private data settings, we address a public data setting where the server has access to the database. Current solutions for this setting either require additional setups (e.g., noncolluding servers, hardware enclaves) or are inefficient for practical workloads. Furthermore,...

With the demand of cryptocurrencies, threshold ECDSA recently regained popularity. So far, several methods have been proposed to construct threshold ECDSA, including the usage of OT and homomorphic encryptions (HE). Due to the mismatch between the plaintext space and the signature space, HE-based threshold ECDSA always requires zero-knowledge range proofs, such as Paillier and Joye-Libert (JL) encryptions. However, the overhead of range proofs constitutes a major portion of the total...

Bootstrapping is the core task in fully homomorphic encryption. It is designed to self-clean encrypted data to support unlimited level of homomorphic computing. FHEW/TFHE cryptosystem provides the fastest bootstrapping machinery in addition to the unique homomorphic evaluation functionality. In 2021, the problem of large-precision bootstrapping was investigated in the literature, with fast algorithms proposed and implemented. A common strategy to all the algorithms is to decompose the...

Homomorphic Encryption (HE) enables operations on encrypted data without requiring decryption, thus allowing for secure handling of confidential data within smart contracts. Among the known HE schemes, FHEW and TFHE are particularly notable for use in smart contracts due to their lightweight nature and support for arbitrary logical gates. In contrast, other HE schemes often require several gigabytes of keys and are limited to supporting only addition and multiplication. As a result, there...

Speed efficiency, memory optimization, and quantum resistance are essential for safeguarding the performance and security of cloud computing environments. Fully Homomorphic Encryption (FHE) addresses this need by enabling computations on encrypted data without requiring decryption, thereby maintaining data privacy. Additionally, lattice-based FHE is quantum secure, providing defense against potential quantum computer attacks. However, the performance of current FHE schemes remains...

In this paper, we introduce a novel approach to Multi-Key Fully Homomorphic Encryption (MK-FHE) that enhances both efficiency and security beyond the capabilities of traditional MK-FHE and MultiParty Computation (MPC) systems. Our method generates a unified key structure, enabling constant ciphertext size and constant execution time for encrypted computations, regardless of the number of participants involved. This approach addresses critical limitations such as ciphertext size expansion,...

In this work, we introduce a more efficient post-quantum oblivious PRF (OPRF) design, called LeOPaRd. Our proposal is round-optimal and supports verifiability and partial obliviousness, all of which are important for practical applications. The main technical novelty of our work is a new method for computing samples of MLWE (Module Learning With Errors) in a two-party setting. To do this, we introduce a new family of interactive lattice problems, called interactive MLWE with re-use...

Homomorphic encryption has long been used to build voting schemes. Additively homomorphic encryption only allows simple count- ing functions. Lattice-based fully (or somewhat) homomorphic encryp- tion allows more general counting functions, but the required parameters quickly become impractical if used naively. It is safe to leak information during the counting function evaluation, as long as the information could be derived from the public result. To exploit this observation, we...