Private set intersection: A systematic literature review

Secure Multi-party Computation (SMPC) is a family of protocols which allow some parties to compute a function on their private inputs, obtaining the output at the end and nothing more. In this work, we focus on a particular SMPC problem named Private Set Intersection (PSI). The challenge in PSI is how two or more parties can compute the intersection of their private input sets, while the elements that are not in the intersection remain private. This problem has attracted the attention of many researchers because of its wide variety of applications, contributing to the proliferation of many different approaches. Despite that, current PSI protocols still require heavy cryptographic assumptions that may be unrealistic in some scenarios. In this paper, we perform a Systematic Literature Review of PSI solutions, with the objective of analyzing the main scenarios where PSI has been studied and giving the reader a general taxonomy of the problem together with a general understanding of the most common tools used to solve it. We also analyze the performance using different metrics, trying to determine if PSI is mature enough to be used in realistic scenarios, identifying the pros and cons of each protocol and the remaining open problems.This work has been partially supported by the projects: BIGPrivDATA (UMA20-FEDERJA-082) from the FEDER Andalucía 2014– 2020 Program and SecTwin 5.0 funded by the Ministry of Science and Innovation, Spain, and the European Union (Next Generation EU) (TED2021-129830B-I00). The first author has been funded by the Spanish Ministry of Education under the National F.P.U. Program (FPU19/01118). Funding for open access charge: Universidad de Málaga/CBU

Adaptive Oblivious Transfer and Generalization

International audienceOblivious Transfer (OT) protocols were introduced in the seminal paper of Rabin, and allow a user to retrieve a given number of lines (usually one) in a database, without revealing which ones to the server. The server is ensured that only this given number of lines can be accessed per interaction, and so the others are protected; while the user is ensured that the server does not learn the numbers of the lines required. This primitive has a huge interest in practice, for example in secure multi-party computation, and directly echoes to Symmetrically Private Information Retrieval (SPIR). Recent Oblivious Transfer instantiations secure in the UC framework suf- fer from a drastic fallback. After the first query, there is no improvement on the global scheme complexity and so subsequent queries each have a global complexity of O(|DB|) meaning that there is no gain compared to running completely independent queries. In this paper, we propose a new protocol solving this issue, and allowing to have subsequent queries with a complexity of O(log(|DB|)), and prove the protocol security in the UC framework with adaptive corruptions and reliable erasures. As a second contribution, we show that the techniques we use for Obliv- ious Transfer can be generalized to a new framework we call Oblivi- ous Language-Based Envelope (OLBE). It is of practical interest since it seems more and more unrealistic to consider a database with uncontrolled access in access control scenarii. Our approach generalizes Oblivious Signature-Based Envelope, to handle more expressive credentials and requests from the user. Naturally, OLBE encompasses both OT and OSBE, but it also allows to achieve Oblivious Transfer with fine grain access over each line. For example, a user can access a line if and only if he possesses a certificate granting him access to such line. We show how to generically and efficiently instantiate such primitive, and prove them secure in the Universal Composability framework, with adaptive corruptions assuming reliable erasures. We provide the new UC ideal functionalities when needed, or we show that the existing ones fit in our new framework. The security of such designs allows to preserve both the secrecy of the database values and the user credentials. This symmetry allows to view our new approach as a generalization of the notion of Symmetrically PIR

Towards compact bandwidth and efficient privacy-preserving computation

In traditional cryptographic applications, cryptographic mechanisms are employed to ensure the security and integrity of communication or storage. In these scenarios, the primary threat is usually an external adversary trying to intercept or tamper with the communication between two parties. On the other hand, in the context of privacy-preserving computation or secure computation, the cryptographic techniques are developed with a different goal in mind: to protect the privacy of the participants involved in a computation from each other. Specifically, privacy-preserving computation allows multiple parties to jointly compute a function without revealing their inputs and it has numerous applications in various fields, including finance, healthcare, and data analysis. It allows for collaboration and data sharing without compromising the privacy of sensitive data, which is becoming increasingly important in today's digital age. While privacy-preserving computation has gained significant attention in recent times due to its strong security and numerous potential applications, its efficiency remains its Achilles' heel. Privacy-preserving protocols require significantly higher computational overhead and bandwidth when compared to baseline (i.e., insecure) protocols. Therefore, finding ways to minimize the overhead, whether it be in terms of computation or communication, asymptotically or concretely, while maintaining security in a reasonable manner remains an exciting problem to work on. This thesis is centred around enhancing efficiency and reducing the costs of communication and computation for commonly used privacy-preserving primitives, including private set intersection, oblivious transfer, and stealth signatures. Our primary focus is on optimizing the performance of these primitives.Im Gegensatz zu traditionellen kryptografischen Aufgaben, bei denen Kryptografie verwendet wird, um die Sicherheit und Integrität von Kommunikation oder Speicherung zu gewährleisten und der Gegner typischerweise ein Außenstehender ist, der versucht, die Kommunikation zwischen Sender und Empfänger abzuhören, ist die Kryptografie, die in der datenschutzbewahrenden Berechnung (oder sicheren Berechnung) verwendet wird, darauf ausgelegt, die Privatsphäre der Teilnehmer voreinander zu schützen. Insbesondere ermöglicht die datenschutzbewahrende Berechnung es mehreren Parteien, gemeinsam eine Funktion zu berechnen, ohne ihre Eingaben zu offenbaren. Sie findet zahlreiche Anwendungen in verschiedenen Bereichen, einschließlich Finanzen, Gesundheitswesen und Datenanalyse. Sie ermöglicht eine Zusammenarbeit und Datenaustausch, ohne die Privatsphäre sensibler Daten zu kompromittieren, was in der heutigen digitalen Ära immer wichtiger wird. Obwohl datenschutzbewahrende Berechnung aufgrund ihrer starken Sicherheit und zahlreichen potenziellen Anwendungen in jüngster Zeit erhebliche Aufmerksamkeit erregt hat, bleibt ihre Effizienz ihre Achillesferse. Datenschutzbewahrende Protokolle erfordern deutlich höhere Rechenkosten und Kommunikationsbandbreite im Vergleich zu Baseline-Protokollen (d.h. unsicheren Protokollen). Daher bleibt es eine spannende Aufgabe, Möglichkeiten zu finden, um den Overhead zu minimieren (sei es in Bezug auf Rechen- oder Kommunikationsleistung, asymptotisch oder konkret), während die Sicherheit auf eine angemessene Weise gewährleistet bleibt. Diese Arbeit konzentriert sich auf die Verbesserung der Effizienz und Reduzierung der Kosten für Kommunikation und Berechnung für gängige datenschutzbewahrende Primitiven, einschließlich private Schnittmenge, vergesslicher Transfer und Stealth-Signaturen. Unser Hauptaugenmerk liegt auf der Optimierung der Leistung dieser Primitiven

Private Set Intersection in the Internet Setting From Lightweight Oblivious PRF

We present a new protocol for two-party private set intersection (PSI) with semi-honest security in the plain model and one-sided malicious security in the random oracle model. Our protocol achieves a better balance between computation and communication than existing PSI protocols. Specifically, our protocol is the fastest in networks with moderate bandwidth (e.g., 30 - 100 Mbps). Considering the monetary cost (proposed by Pinkas et al. in CRYPTO 2019) to run the protocol on a cloud computing service, our protocol also compares favorably. Underlying our PSI protocol is a new lightweight multi-point oblivious pesudorandom function (OPRF) protocol based on oblivious transfer (OT) extension. We believe this new protocol may be of independent interest

Privacy preserving linkage and sharing of sensitive data

2018 Summer.Includes bibliographical references.Sensitive data, such as personal and business information, is collected by many service providers nowadays. This data is considered as a rich source of information for research purposes that could benet individuals, researchers and service providers. However, because of the sensitivity of such data, privacy concerns, legislations, and con ict of interests, data holders are reluctant to share their data with others. Data holders typically lter out or obliterate privacy related sensitive information from their data before sharing it, which limits the utility of this data and aects the accuracy of research. Such practice will protect individuals' privacy; however it prevents researchers from linking records belonging to the same individual across dierent sources. This is commonly referred to as record linkage problem by the healthcare industry. In this dissertation, our main focus is on designing and implementing ecient privacy preserving methods that will encourage sensitive information sources to share their data with researchers without compromising the privacy of the clients or aecting the quality of the research data. The proposed solution should be scalable and ecient for real-world deploy- ments and provide good privacy assurance. While this problem has been investigated before, most of the proposed solutions were either considered as partial solutions, not accurate, or impractical, and therefore subject to further improvements. We have identied several issues and limitations in the state of the art solutions and provided a number of contributions that improve upon existing solutions. Our rst contribution is the design of privacy preserving record linkage protocol using semi-trusted third party. The protocol allows a set of data publishers (data holders) who compete with each other, to share sensitive information with subscribers (researchers) while preserving the privacy of their clients and without sharing encryption keys. Our second contribution is the design and implementation of a probabilistic privacy preserving record linkage protocol, that accommodates discrepancies and errors in the data such as typos. This work builds upon the previous work by linking the records that are similar, where the similarity range is formally dened. Our third contribution is a protocol that performs information integration and sharing without third party services. We use garbled circuits secure computation to design and build a system to perform the record linkages between two parties without sharing their data. Our design uses Bloom lters as inputs to the garbled circuits and performs a probabilistic record linkage using the Dice coecient similarity measure. As garbled circuits are known for their expensive computations, we propose new approaches that reduce the computation overhead needed, to achieve a given level of privacy. We built a scalable record linkage system using garbled circuits, that could be deployed in a distributed computation environment like the cloud, and evaluated its security and performance. One of the performance issues for linking large datasets is the amount of secure computation to compare every pair of records across the linked datasets to nd all possible record matches. To reduce the amount of computations a method, known as blocking, is used to lter out as much as possible of the record pairs that will not match, and limit the comparison to a subset of the record pairs (called can- didate pairs) that possibly match. Most of the current blocking methods either require the parties to share blocking keys (called blocks identiers), extracted from the domain of some record attributes (termed blocking variables), or share reference data points to group their records around these points using some similarity measures. Though these methods reduce the computation substantially, they leak too much information about the records within each block. Toward this end, we proposed a novel privacy preserving approximate blocking scheme that allows parties to generate the list of candidate pairs with high accuracy, while protecting the privacy of the records in each block. Our scheme is congurable such that the level of performance and accuracy could be achieved according to the required level of privacy. We analyzed the accuracy and privacy of our scheme, implemented a prototype of the scheme, and experimentally evaluated its accuracy and performance against dierent levels of privacy

SpOT-Light: Lightweight Private Set Intersection from Sparse OT Extension

We describe a novel approach for two-party private set intersection (PSI) with semi-honest security. Compared to existing PSI protocols, ours has a more favorable balance between communication and computation. Specifically, our protocol has the lowest monetary cost of any known PSI protocol, when run over the Internet using cloud-based computing services (taking into account current rates for CPU + data). On slow networks (e.g., 10Mbps) our protocol is actually the fastest. Our novel underlying technique is a variant of oblivious transfer (OT) extension that we call sparse OT extension. Conceptually it can be thought of as a communication-efficient multipoint oblivious PRF evaluation. Our sparse OT technique relies heavily on manipulating high-degree polynomials over large finite fields (i.e. elements whose representation requires hundreds of bits). We introduce extensive algorithmic and engineering improvements for interpolation and multi-point evaluation of such polynomials, which we believe will be of independent interest. Finally, we present an extensive empirical comparison of state-of-the- art PSI protocols in several application scenarios and along several dimensions of measurement: running time, communication, peak memory consumption, and — arguably the most relevant metric for practice — monetary cos

Unbalanced Circuit-PSI from Oblivious Key-Value Retrieval

Circuit-based Private Set Intersection (circuit-PSI) enables two parties, a client and a server, with their input sets $X$ and $Y$ respectively, to securely compute a function $f$ on the intersection $X \cap Y$, while keeping $X \cap Y$ secret from both parties. Although several computationally efficient circuit-PSI protocols have been proposed recently, they most focus on the balanced scenario where $|X|$ is similar to $|Y|$. However, in many realistic scenarios, a circuit-PSI protocol may be performed in the unbalanced case where $|X|$ is remarkably smaller than $|Y|$ (e.g., the client is a constrained device holding a small set, while the server is a service provider holding a large set). Directly applying existing protocols to this scenario will lead to significant efficiency issues because the communication complexity of the protocols scales at least linearly with the size of the larger set, i.e., $\max(|X|, |Y|)$. In this work, we put forth efficient constructions for unbalanced circuit-PSI with sublinear communication complexity in the size of the larger set. The main insight is that we formalize unbalanced circuit-PSI as obliviously retrieving values corresponding to keys from a set of key-value pairs. To this end, we present a new functionality called Oblivious Key-Value Retrieval (OKVR) and design the OKVR protocol from a new notion called sparse Oblivious Key-Value Stores (sparse OKVS). We conduct extensive experiments and the results show that our constructions remarkably outperform the state-of-the-art circuit-PSI schemes (EUROCRYPT\u2719, PETs\u2722, CCS\u2722), i.e., $1.84 \sim 48.86 \times$ communication improvement and $1.50 \sim39.81 \times$ faster computation. Very recently, Son and Jeong (AsiaCCS\u2723) also present unbalanced circuit-PSI protocols, and our constructions outperform them by $1.18 \sim 15.99 \times$ and $1.22 \sim 10.44 \times$ in communication and computation overhead, respectively, depending on set sizes and network environments