What a lovely hat

Collecting statistics from users of software and online services is crucial to improve service quality, yet obtaining such insights while preserving individual privacy remains a challenge. Recent advances in function secret sharing (FSS) make it possible for scalable privacy-preserving measurement (PPM), which leads to ongoing standardization at the IETF. However, FSS-based solutions still face several challenges for streaming analytics, where messages are continuously sent, and secure...

Fully Homomorphic encryption (FHE) allows computation without decryption, but often suffers from a ciphertext expansion ratio and overhead. On the other hand, AES is a widely adopted symmetric block cipher known for its efficiency and compact ciphertext size. However, its symmetric nature prevents direct computation on encrypted data. Homomorphic transciphering bridges these two approaches by enabling computation on AES-encrypted data using FHE-encrypted AES keys, thereby combining the...

We present the first systematic study on communication-efficient evaluation of the lightweight cipher family Ascon within secure multi-party computation (MPC). By leveraging Ascon’s parallel, bit-oriented structure, we adapt its design using Reverse Multiplication-Friendly Embeddings (RMFEs, introduced by Cascudo et al.\ in CRYPTO'18) in a single-circuit evaluation, enabling efficient packing of groups of bits into field elements. Our protocol, which uses relatively small RMFEs,...

The dream of achieving data privacy during external computations has become increasingly concrete in recent years. Indeed, since the early days of Fully Homomorphic Encryption (FHE) more than a decade ago, new cryptosystems and techniques have constantly optimized the efficiency of computation on encrypted data. However, one of the main disadvantages of FHE, namely its significant ciphertext expansion factor, remains at the center of the efficiency bottleneck of FHE schemes. To tackle the...

Fully Homomorphic Encryption (FHE) enables arbitrary computation directly on encrypted data. The TFHE scheme supports encryption of bits or small integers, evaluating any univariate function via programmable bootstrapping (PBS), which also refreshes ciphertext noise. Since both linear and nonlinear functions can be expressed with PBS, arbitrary circuits of unlimited depth can be computed without accuracy loss, aside from a negligible failure probability. However, a key limitation of TFHE is...

Private information retrieval (PIR) allows a client to query a public database privately and serves as a key building block for privacy-enhancing applications. Minimizing query size is particularly important in many use cases, for example when clients operate on low-power or bandwidth-constrained devices. However, existing PIR protocols exhibit large query sizes: to query $2^{25}$ records, the smallest query size of 14.8KB is reported in Respire [Burton et al., CCS'24]. Respire is based on...

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...

Fully Homomorphic Encryption (FHE) allows computations on encrypted data without requiring decryption, ensuring data privacy during processing. However, FHE introduces a significant expansion of ciphertext sizes compared to plaintexts, which results in higher communication. A practical solution to mitigate this issue is transciphering, where only the master key is homomorphically encrypted, while the actual data is encrypted using a symmetric cipher, usually a stream cipher. The server...

Data privacy concerns are sharply rising in the current digital era, hyperdriven by cloud computing, big data analytics, and the Internet of Things. Homomorphic Encryption (HE) has emerged as an ideal technique for computing on encrypted data, but current schemes suffer from slow encryption speed and large ciphertext expansion. Practical implementation is hindered, especially when the client has limited bandwidth, memory, and computing power. In 2011, Naehrig et al. proposed transciphering,...

Making the most of TFHE advanced capabilities such as programmable or circuit bootstrapping and their generalizations for manipulating data larger than the native plaintext domain of the scheme is a very active line of research. In this context, AES is a particularly interesting benchmark, as an example of a nontrivial algorithm which has eluded "practical" FHE execution performances for years, as well as the fact that it will most likely be selected by NIST as a flagship reference in its...

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...

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...

Fully Homomorphic Encryption (FHE) is a powerful technology that allows a cloud server to perform computations directly on ciphertexts. To overcome the overhead of sending and storing large FHE ciphertexts, the concept of FHE transciphering was introduced, allowing symmetric key encrypted ciphertexts to be transformed into FHE ciphertexts by deploying symmetric key decryption homomorphically. However, existing FHE transciphering schemes remain unauthenticated and malleable, allowing...

TFHE is a fully homomorphic encryption scheme over the torus that supports fast bootstrapping. Its primary evaluation mechanism is based on gate bootstrapping and programmable bootstrapping (PBS), which computes functions while simultaneously refreshing noise. PBS-based evaluation is user-friendly and efficient for small circuits; however, the number of bootstrapping operations increases exponentially with the circuit depth. To address the challenge of efficiently evaluating large-scale...

The Rasta design strategy allows building low-round ciphers due to its efficient prevention of statistical attacks and algebraic attacks by randomizing the cipher, which makes it especially suitable for hybrid homomorphic encryption (HHE), also known as transciphering. Such randomization is obtained by pseudorandomly sampling new invertible matrices for each round of each new cipher evaluation. However, naively sampling a random invertible matrix for each round significantly impacts the...

A transciphering framework, also known as hybrid homomorphic encryption, is a practical method of combining a homomorphic encryption~(HE) scheme with a symmetric cipher in the client-server model to reduce computational and communication overload on the client side. As a server homomorphically evaluates a symmetric cipher in this framework, new design rationales are required for ``HE-friendly'' ciphers that take into account the specific properties of the HE schemes. In this paper, we...

Certain applications of fully homomorphic encryption (such as transciphering, universal thresholdizers, PIR, and ORAM) require randomness while operating over encrypted data. This randomness has to beobliviously generated in the encrypted domain and remain encrypted throughout the computation. Moreover, it should be guaranteed that independent-looking random coins can be obliviously generated for different computations. In this work, we consider the homomorphic evaluation of pseudorandom...

We present a new method for efficient look-up table (LUT) evaluation in homomorphic encryption (HE), based on Ring-LWE-based HE schemes, including both integer-message schemes such as Brakerski-Gentry-Vaikuntanathan (BGV) and Brakerski/Fan-Vercauteren (BFV), and complex-number-message schemes like the Cheon-Kim-Kim-Song (CKKS) scheme. Our approach encodes bit streams into codewords and translates LUTs into low-degree multivariate polynomials, allowing for the simultaneous evaluation of...

Fully Homomorphic Encryption offers an effective solution for privacy-preserving computation, but its adoption is hindered by substantial computational and communication overheads. To address these, the Hybrid Homomorphic Encryption (HHE) protocol was developed, where the client encrypts data using a symmetric encryption scheme (SE), and the server homomorphically evaluates its decryption. Previous studies have demonstrated that the HHE protocol has no impact on the correctness of...

Fully homomorphic encryption (FHE) is an advanced cryptography technique to allow computations (i.e., addition and multiplication) over encrypted data. After years of effort, the performance of FHE has been significantly improved and it has moved from theory to practice. The transciphering framework is another important technique in FHE to address the issue of ciphertext expansion and reduce the client-side computational overhead. To apply the transciphering framework to the CKKS FHE scheme,...

Fully Homomorphic Encryption (FHE) is a powerful tool to achieve non-interactive privacy preserving protocols with optimal computation/communication complexity. However, the main disadvantage is that the actual communication cost (bandwidth) is high due to the large size of FHE ciphertexts. As a solution, a technique called transciphering (also known as Hybrid Homomorphic Encryption) was introduced to achieve almost optimal bandwidth for such protocols. However, all of existing works require...

Secure multi-party computation (MPC) enables multiple distrusting parties to compute a function while keeping their respective inputs private. In a threshold implementation of a symmetric primitive, e.g., of a block cipher, each party holds a share of the secret key or of the input block. The output block is computed without reconstructing the secret key. This enables the construction of distributed TPMs or transciphering for secure data transmission in/out of the MPC context. This paper...

IoT devices collect privacy-sensitive data, e.g., in smart grids or in medical devices, and send this data to cloud servers for further processing. In order to ensure confidentiality as well as authenticity of the sensor data in the untrusted cloud environment, we consider a transciphering scenario between embedded IoT devices and multiple cloud servers that perform secure multi-party computation (MPC). Concretely, the IoT devices encrypt their data with a lightweight symmetric cipher and...

Most of the current fully homomorphic encryption (FHE) schemes are based on either the learning-with-errors (LWE) problem or on its ring variant (RLWE) for storing plaintexts. During the homomorphic computation of FHE schemes, RLWE formats provide high throughput when considering several messages, and LWE formats provide a low latency when there are only a few messages. Efficient conversion can bridge the advantages of each format. However, converting LWE formats into RLWE format, which is...

Fully homomorphic encryption suffers from a large expansion in the size of encrypted data, which makes FHE impractical for low-bandwidth networks. Fortunately, transciphering allows to circumvent this issue by involving a symmetric cryptosystem which does not carry the disadvantage of a large expansion factor, and maintains the ability to recover an FHE ciphertext with the cost of extra homomorphic computations on the receiver side. Recent works have started to investigate the efficiency of...

Homomorphic encryption (HE) enables computation delegation to untrusted third parties while maintaining data confidentiality. Hybrid encryption (a.k.a transciphering) allows a reduction in the number of ciphertexts and storage size, which makes FHE solutions practical for a variety of modern applications. Still, modern transciphering has three main drawbacks: 1) lack of standardization or bad performance of symmetric decryption under FHE; 2) post-HE-evaluation is limited to small-size...

Since the pioneering work of Gentry, Halevi, and Smart in 2012, the state of the art on transciphering has moved away from work on AES to focus on new symmetric algorithms that are better suited for a homomorphic execution. Yet, with recent advances in homomorphic cryptosystems, the question arises as to where we stand today. Especially since AES execution is the application that may be chosen by NIST in the FHE part of its future call for threshold encryption. In this paper, we propose an...

We present a reactive MPC protocol built from FHE which is robust in the presence of active adversaries. In addition the protocol enables reduced bandwidth via means of transciphering, and also enables more expressive/efficient programs via means of a $\mathsf{Declassify}$ operation. All sub-components of the protocol can be efficiently realised using existing technology. We prove our protocol secure in the UC framework.

We examine the use of Trivium and Kreyvium as transciphering mechanisms for use with the TFHE FHE scheme. Originally these two ciphers were investigated for FHE transciphering only in the context of the BGV/BFV FHE schemes; this is despite Trivium and Kreyvium being particarly suited to TFHE. Recent work by Dobraunig et al. gave some initial experimental results using TFHE. We show that these two symmetric ciphers have excellent performance when homomorphically evaluated using TFHE. Indeed...

Symmetric primitives are a cornerstone of cryptography, and have traditionally been defined over fields, where cryptanalysis is now well understood. However, a few symmetric primitives defined over rings Z_q for a composite number q have recently been proposed, a setting where security is much less studied. In this paper we focus on studying established algebraic attacks typically defined over fields and the extent of their applicability to symmetric primitives defined over the ring of...

Fully homomorphic encryption (FHE) is a powerful cryptographic technique allowing to perform computation directly over encrypted data. Motivated by the overhead induced by the homomorphic ciphertexts during encryption and transmission, the transciphering technique, consisting in switching from a symmetric encryption to FHE encrypted data was investigated in several papers. Different stream and block ciphers were evaluated in terms of their "FHE-friendliness", meaning practical...

Machine learning as a service scenario typically requires the client to trust the server and provide sensitive data in plaintext. However, with the recent improvements in fully homomorphic encryption (FHE) schemes, many such applications can be designed in a privacy preserving way. In this work, we focus on such a problem, private decision tree evaluation (PDTE) --- where a server has a decision tree classification model, and a client wants to use the model to classify her private data...

The Recent progress in practical applications of secure computation protocols has also attracted attention to the symmetric-key primitives underlying them. Whereas traditional ciphers have evolved to be efficient with respect to certain performance metrics, advanced cryptographic protocols call for a different focus. The so called arithmetic complexity is viewed through the number and layout of non-linear operations in the circuit implemented by the protocol. Symmetric-key algorithms that...

A transciphering framework converts a symmetric ciphertext into a homomorphic ciphertext on the server-side, reducing computational and communication overload on the client-side. In Asiacrypt 2021, Cho et al. proposed the RtF framework that supports approximate computation. In this paper, we propose a family of noisy ciphers, dubbed Rubato, with a novel design strategy of introducing noise to a symmetric cipher of a low algebraic degree. With this strategy, the multiplicative complexity...

Improved filter permutators are designed to build stream ciphers that can be efficiently evaluated homomorphically. So far the transciphering with such ciphers has been implemented with homomorphic schemes from the second generation. In theory the third generation is more adapted for the particular design of these ciphers. In this article we study how suitable it is in practice. We implement the transciphering of different instances of the stream cipher family FiLIP with homomorphic...

Homomorphic encryption (HE) is a promising cryptographic primitive that enables computation over encrypted data, with a variety of applications including medical, genomic, and financial tasks. In Asiacrypt 2017, Cheon et al. proposed the CKKS scheme to efficiently support approximate computation over encrypted data of real numbers. HE schemes including CKKS, nevertheless, still suffer from slow encryption speed and large ciphertext expansion compared to symmetric cryptography. In this...