Efficient Protocols for Oblivious Linear Function Evaluation from Ring-LWE

An oblivious linear function evaluation protocol, or OLE, is a two-party protocol for the function $f(x) = ax + b$, where a sender inputs the field elements $a,b$, and a receiver inputs $x$ and learns $f(x)$. OLE can be used to build secret-shared multiplication, and is an essential component of many secure computation applications including general-purpose multi-party computation, private set intersection and more. In this work, we present several efficient OLE protocols from the ring learning with errors (RLWE) assumption. Technically, we build two new passively secure protocols, which build upon recent advances in homomorphic secret sharing from (R)LWE (Boyle et al., Eurocrypt 2019), with optimizations tailored to the setting of OLE. We upgrade these to active security using efficient amortized zero-knowledge techniques for lattice relations (Baum et al., Crypto 2018), and design new variants of zero-knowledge arguments that are necessary for some of our constructions. Our protocols offer several advantages over existing constructions. Firstly, they have the lowest communication complexity amongst previous, practical protocols from RLWE and other assumptions; secondly, they are conceptually very simple, and have just one round of interaction for the case of OLE where $b$ is randomly chosen. We demonstrate this with an implementation of one of our passively secure protocols, which can perform more than 1 million OLEs per second over the ring $\mathbb{Z}_m$, for a 120-bit modulus $m$, on standard hardware

Secure Poisson Regression

We introduce the first construction for secure two-party computation of Poisson regression, which enables two parties who hold shares of the input samples to learn only the resulting Poisson model while protecting the privacy of the inputs. Our construction relies on new protocols for secure fixed-point exponentiation and correlated matrix multiplications. Our secure exponentiation construction avoids expensive bit decomposition and achieves orders of magnitude improvement in both online and offline costs over state of the art works. As a result, the dominant cost for our secure Poisson regression are matrix multiplications with one fixed matrix. We introduce a new technique, called correlated Beaver triples, which enables many such multiplications at the cost of roughly one matrix multiplication. This further brings down the cost of secure Poisson regression. We implement our constructions and show their extreme efficiency. In a LAN setting, our secure exponentiation for 20-bit fractional precision takes less than 0.07ms with a batch-size of 100,000. One iteration of secure Poisson regression on a dataset with 10,000 samples with 1000 binary features needs about 65.82s in the offline phase, 55.14s in the online phase and 17MB total communication. For several real datasets this translates into training that takes seconds and only a couple of MB communication

Construction of Communication Protocol Using Ring-LWE-Based Homomorphic Encryption in Iot-Cloud Environment

The rapid development of wireless communication and sensor networks is the basis for forming an Internet of things(IoT) infrastructure. In IoT-based applications, the cryptographic encryption and access control at cloud must be robust to withstand current attacks. The majority of security protocols are based on integer factorization and discrete logarithm problems, which are proved vulnerable to quantum attacks. In this paper, we proposed a scheme for the security and privacy of the user data in a cloud environment. Various types of homomorphic encryption schemes are studied for data privacy in the cloud. The Ring-LWE-based encryption scheme is presented for privacy protection in the cloud which meets the homomorphic properties. The scheme is analysed for security, privacy, reduced messaging overhead and computation overhead. The objective of this paper is to Design and Construct a Ring-LWE-based homomorphic encryption(HE) communication protocol for authenticated user message encryption in a IoT cloud computing environment. The evaluation function in holomorphic encryption defined based on Ring-LWE encryption for a practical sharing-enabled cloud storage. Then, formally proving the security of the proposed protocol for classical and quantum attacks in cloud environment like Manin-the-middle (MITM) attack, Denial of Service (DoS) and Replay Attack

Diogenes: Lightweight Scalable RSA Modulus Generation with a Dishonest Majority

In this work, we design and implement the first protocol for RSA modulus construction that can support thousands of parties and offers security against an arbitrary number of corrupted parties. In a nutshell, we design the ``best\u27\u27 protocol for this scale that is secure against passive corruption, then amplify it to obtain active security using efficient non-interactive zero-knowledge arguments. Our protocol satisfies a stronger security guarantee where a deviating party can be identified when the protocol aborts (referred to as security with identifiable-abort) and allows for ``public verifiability\u27\u27. Our passively secure protocol extends the recent work of Chen et al. that, in turn, is based on the blueprint introduced in the original work of Boneh-Franklin protocol (CRYPTO 1997, J. ACM, 2001). Specifically, we reduce the task of sampling a modulus to secure distributed multiplication, which we implement via an efficient threshold additively homomorphic encryption (AHE) scheme based on the Ring-LWE assumption. This results in a protocol where the amortized per-party communication cost grows logarithmically in the number of parties. In order to keep the parties lightweight, we employ an ``untrusted\u27\u27 coordinator that is connected to all parties and performs all public and broadcast operations. We amplify this protocol to obtain active security (with identifiable-abort) by attaching zero-knowledge proofs. We instantiate our ZK proof system by composing two different types of ZK proof systems: (1) the Ligero sub-linear zero-knowledge proof system (Ames et al., CCS 2017), and (2) Sigma-protocol for proving the knowledge of a discrete logarithm in unknown order groups (Shoup, Eurocrypt 2000). We implemented both the passive and the active variants of our protocol and ran experiments using 2 to 4,000 parties. This is the first such implementation of any MPC protocol that can scale to more than 1,000 parties. For generating a 2048-bit modulus among 1,000 parties, our passive protocol executed in under 4 minutes and the active variant ran in 22 minutes

BumbleBee: Secure Two-party Inference Framework for Large Transformers

Large transformer-based models have realized state- of-the-art performance on lots of real-world tasks such as natural language processing and computer vision. However, with the increasing sensitivity of the data and tasks they handle, privacy has become a major concern during model deployment. In this work, we focus on private inference in two-party settings, where one party holds private inputs and the other holds the model. We introduce BumbleBee, a fast and communication-friendly two-party private transformer inference system. Our contributions are three-fold: Firstly, we present optimized homomorphic encryption-based proto- cols that enable the multiplication of large matrices with 80 – 90% less communication cost than existing methods. Secondly, we offer a general method for designing efficient and accurate protocols for non-linear activation functions in transformers. Our activation protocols have demonstrated speed and reduced the communication overhead by 80 – 95% over two existing methods. Finally, we conducted intensive benchmarks on several large transformer models. Results show that BumbleBee is more than one order of magnitude faster than Iron (NeurIPS22)

Efficient Privacy Preserving Logistic Regression Inference and Training

Recently, privacy-preserving logistic regression techniques on distributed data among several data owners drew attention in terms of their applicability in federated learning environment. Many of them have been built upon cryptographic primitives such as secure multiparty computations(MPC) and homomorphic encryptions(HE) to protect the privacy of data. The secure multiparty computation provides fast and secure unit operations for arithmetic and bit operations but they often does not scale with large data well enough due to large computation cost and communication overhead. From recent works, many HE primitives provide their operations in a batch sense so that the technique can be an appropriate choice in a big data environment. However computationally expensive operations such as ciphertext slot rotation or refreshment(so called bootstrapping) and large public key size are hurdles that hamper widespread of the technique in the industry-level environment. In this paper, we provide a new hybrid approach of a privacy-preserving logistic regression training and a inference, which utilizes both MPC and HE techniques to provide efficient and scalable solution while minimizing needs of key management and complexity of computation in encrypted state. Utilizing batch sense properties of HE, we present a method to securely compute multiplications of vectors and matrices using one HE multiplication, compared to the naive approach which requires linear number of multiplications regarding to the size of input data. We also show how we used a 2-party additive secret sharing scheme to control noises of expensive HE operations such as bootstrapping efficiently

FAPRIL: Towards Faster Privacy-Preserving Fingerprint-Based Localization

Fingerprinting is a commonly used technique to provide accurate localization for indoor areas, where global navigation satellite systems, such as GPS and Galileo, cannot function or are not precise enough. Although fingerprint-based indoor localization has gained wide popularity, existing solutions that preserve privacy either rely on non-colluding servers or have high communication which hinder deployment. In this work we present FAPRIL, a privacy-preserving indoor localization scheme, which takes advantage of the latest secure two-party computation protocol improvements. We can split our scheme into two parts: an input independent setup phase and an online phase. We concentrate on optimizing the online phase for mobile clients who run on a mobile data plan and observe that recurring operands allow to optimize the total communication overhead even further. Our observation can be generalized, e.g., to improve multiplication of Arithmetic secret shared matrices. We implement FAPRIL on mobile devices and our benchmarks over a simulated LTE network show that the online phase of a private localization takes under 0.15 seconds with less than 0.20 megabytes of communication even for large buildings. The setup phase, which can be pre-computed, depends heavily on the setting but stays in the range 0.28 - 4.14 seconds and 0.69 - 16.00 megabytes per localization query. The round complexity of FAPRIL is constant for both phases

Overdrive2k: Efficient Secure MPC over Z2kZ_{2^k} from Somewhat Homomorphic Encryption

Recently, Cramer et al. (CRYPTO 2018) presented a protocol, SPDZ2k, for actively secure multiparty computation for dishonest majority in the pre-processing model over the ring $Z_{2^k}$, instead of over a prime field $F_p$. Their technique used oblivious transfer for the pre-processing phase, more specifically the MASCOT protocol (Keller et al. CCS 2016). In this paper we describe a more efficient technique for secure multiparty computation over $Z_{2^k}$ based on somewhat homomorphic encryption. In particular we adapt the Overdrive approach (Keller et al. EUROCRYPT 2018) to obtain a protocol which is more like the original SPDZ protocol (Damgård et al. CRYPTO 2012). To accomplish this we introduce a special packing technique for the BGV encryption scheme operating on the plaintext space defined by the SPDZ2k protocol, extending the ciphertext packing method used in SPDZ to the case of $Z_{2^k}$. We also present a more complete pre-processing phase for secure computation modulo $2^k$ by adding a new technique to produce shared random bits. These are needed in a number of online protocols and are quite expensive to generate using the MASCOT-based method given in the original SPDZ2k paper. Our approach can be applied to the High-Gear variant of Overdrive, leading to a protocol whose overall efficiency is up to three times better than the OT-based methodology

Studies on the Security of Selected Advanced Asymmetric Cryptographic Primitives

The main goal of asymmetric cryptography is to provide confidential communication, which allows two parties to communicate securely even in the presence of adversaries. Ever since its invention in the seventies, asymmetric cryptography has been improved and developed further, and a formal security framework has been established around it. This framework includes different security goals, attack models, and security notions. As progress was made in the field, more advanced asymmetric cryptographic primitives were proposed, with other properties in addition to confidentiality. These new primitives also have their own definitions and notions of security. This thesis consists of two parts, where the first relates to the security of fully homomorphic encryption and related primitives. The second part presents a novel cryptographic primitive, and defines what security goals the primitive should achieve. The first part of the thesis consists of Article I, II, and III, which all pertain to the security of homomorphic encryption schemes in one respect or another. Article I demonstrates that a particular fully homomorphic encryption scheme is insecure in the sense that an adversary with access only to the public material can recover the secret key. It is also shown that this insecurity mainly stems from the operations necessary to make the scheme fully homomorphic. Article II presents an adaptive key recovery attack on a leveled homomorphic encryption scheme. The scheme in question claimed to withstand precisely such attacks, and was the only scheme of its kind to do so at the time. This part of the thesis culminates with Article III, which is an overview article on the IND-CCA1 security of all acknowledged homomorphic encryption schemes. The second part of the thesis consists of Article IV, which presents Vetted Encryption (VE), a novel asymmetric cryptographic primitive. The primitive is designed to allow a recipient to vet who may send them messages, by setting up a public filter with a public verification key, and providing each vetted sender with their own encryption key. There are three different variants of VE, based on whether the sender is identifiable to the filter and/or the recipient. Security definitions, general constructions and comparisons to already existing cryptographic primitives are provided for all three variants.Doktorgradsavhandlin

FLUTE: Fast and Secure Lookup Table Evaluations (Full Version)

The concept of using Lookup Tables (LUTs) instead of Boolean circuits is well-known and been widely applied in a variety of applications, including FPGAs, image processing, and database management systems. In cryptography, using such LUTs instead of conventional gates like AND and XOR results in more compact circuits and has been shown to substantially improve online performance when evaluated with secure multi-party computation. Several recent works on secure floating-point computations and privacy-preserving machine learning inference rely heavily on existing LUT techniques. However, they suffer from either large overhead in the setup phase or subpar online performance. We propose FLUTE, a novel protocol for secure LUT evaluation with good setup and online performance. In a two-party setting, we show that FLUTE matches or even outperforms the online performance of all prior approaches, while being competitive in terms of overall performance with the best prior LUT protocols. In addition, we provide an open-source implementation of FLUTE written in the Rust programming language, and implementations of the Boolean secure two-party computation protocols of ABY2.0 and silent OT. We find that FLUTE outperforms the state of the art by two orders of magnitude in the online phase while retaining similar overall communication