Reverse firewalls (RFs), introduced by Mironov and Stephens Davidowitz at Eurocrypt 2015, provide a defence mechanism for cryptographic protocols against subversion attacks. In a subversion setting, an adversary compromises the machines of honest parties, enabling the leakage of their secrets through the protocol transcript. Previous research in this area has established robust guarantees, including resistance against data exfiltration for an RF. In this work, we present a new perspective...

Consider a weak analyst that wishes to outsource data collection and computation of aggregate statistics over a a potentially large population of (also weak) clients to a powerful server. For flexibility and efficiency, we consider public-key and non-interactive protocols, meaning the clients know the analyst's public key but do not share secrets, and each client sends at most one message. Furthermore, the final step should be silent, whereby the analyst simply downloads the (encrypted)...

Zero-Knowledge Succinct Non-interactive Arguments of Knowledge (zkSNARKs) lead to proofs that can be succinctly verified but require huge computational resources to generate. Prior systems outsource proof generation either through public delegation, which reveals the witness to the third party, or, more preferably, private delegation that keeps the witness hidden using multiparty computation (MPC). However, current private delegation schemes struggle with scalability and efficiency due to...

We address the problem of proving the validity of computation on ciphertexts of homomorphic encryption (HE) schemes, a feature that enables outsourcing of data and computation while ensuring both data privacy and integrity. We propose a new solution that handles computations in RingLWE-based schemes, particularly the CKKS scheme for approximate arithmetic. Our approach efficiently handles ciphertext arithmetic in the polynomial ring $R_q$ without emulation overhead and manages ciphertexts...

Fully Homomorphic Encryption (FHE) enables computations on encrypted data, ensuring privacy for outsourced computation. However, verifying the integrity of FHE computations remains a significant challenge, especially for bootstrapping, the most computationally intensive operation in FHE. Prior approaches, including zkVM-based solutions and general-purpose SNARKs, suffer from inefficiencies, with proof generation times ranging from several hours to days. In this work, we propose HasteBoots, a...

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...

With the development of decentralized identity (DID), anonymous credential (AC) technology, as well as its traceability, is receiving more and more attention. Most works introduce a trusted party (regulator) that holds a decryption key or backdoor to directly deanonymize the user identity of anonymous authentication. While some cryptographic primitives can help regulators handle complex tracing tasks among large amounts of user profiles (stored by the issuer) and authentication records...

The adoption of Homomorphic Encryption (HE) and Secure Function Evaluation (SFE) applications in the real world remains lim- ited, even nearly 50 years after the introduction of HE. This is particu- larly unfortunate given the strong privacy and confidentiality guarantees these tools can offer to modern digital life. While attempting to incorporate a simple straw-man PSI protocol into a web service for matching individuals based on their profiles, we en- countered several shortcomings...

The notion of funcCPA security for homomorphic encryption schemes was introduced by Akavia \textit{et~al.}\ (TCC 2022). Whereas it aims to capture the bootstrapping technique in homomorphic encryption schemes, Dodis \textit{et~al.}\ (TCC 2023) pointed out that funcCPA security can also be applied to non-homomorphic public-key encryption schemes (PKE). As an example, they presented a use case for privacy-preserving outsourced computation without homomorphic computation. It should be noted...

Searchable encryption (SE) has been widely studied for cloud storage systems, allowing data encrypted search and retrieval. However, existing SE schemes can not support the fine-grained searchability revocation, making it impractical for real applications. Puncturable encryption (PE) [Oakland'15] can revoke the decryption ability of a data receiver for a specific message, which can potentially alleviate this issue. Moreover, the threat of quantum computing remains an important and realistic...

The rising demand for data privacy in cloud-based environments has led to the development of advanced mechanisms for securely managing sensitive information. A prominent solution in this domain is the "Data Privacy Vault," a concept that is being provided commercially by companies such as Hashicorp, Basis Theory, Skyflow Inc., VGS, Evervault, Protegrity, Anonomatic, and BoxyHQ. However, no existing work has rigorously defined the security notions required for a Data Privacy Vault or proven...

Information-theoretic or unconditional security provides the highest level of security --- independent of the computational capability of an adversary. Secret-sharing techniques achieve information-theoretic security by splitting a secret into multiple parts (called shares) and storing the shares across non-colluding servers. However, secret-sharing-based solutions suffer from high overheads due to multiple communication rounds among servers and/or information leakage due to access-patterns...

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...

We extend the concept of access control for functional encryption, introduced by Abdalla et al. (ASIACRYPT 2020), to function-revealing encryption (Joy and Passelègue, SCN 2018). Here “access control” means that function evaluation is only possible when a specified access policy is met. Specifically, we introduce access-controlled inner product function-revealing encryption (AC-IPFRE) and give two applications. On the theoretical side, we use AC-IPFRE to show that function-hiding...

Searchable symmetric encryption (SSE) enables queries over symmetrically encrypted databases. To achieve practical efficiency, SSE schemes incur a certain amount of leakage; however, this leads to the possibility of leakage cryptanalysis, i.e., cryptanalytic attacks that exploit the leakage from the target SSE scheme to subvert its data and query privacy guarantees. Leakage cryptanalysis has been widely studied in the context of SSE schemes supporting either keyword queries or range queries,...

Privacy-preserving blockchains and private messaging services that ensure receiver-privacy face a significant UX challenge: each client must scan every payload posted on the public bulletin board individually to avoid missing messages intended for them. Oblivious Message Retrieval (OMR) addresses this issue by securely outsourcing this expensive scanning process to a service provider using Homomorphic Encryption (HE). In this work, we propose a new OMR scheme that substantially improves...

Zero-knowledge Succinct Non-interactive Argument of Knowledge (zkSNARK) is a powerful cryptographic primitive, in which a prover convinces a verifier that a given statement is true without leaking any additional information. However, existing zkSNARKs suffer from high computation overhead in the proof generation. This limits the applications of zkSNARKs, such as private payments, private smart contracts, and anonymous credentials. Private delegation has become a prominent way to accelerate...

Fully Homomorphic Encryption (FHE) is a promising privacy-enhancing technique that enables secure and private data processing on untrusted servers, such as privacy-preserving neural network (NN) evaluations. However, its practical application presents significant challenges. Limitations in how data is stored within homomorphic ciphertexts and restrictions on the types of operations that can be performed create computational bottlenecks. As a result, a growing body of research focuses on...

We show that the outsourcing algorithm for the case of linear constraints [IEEE Trans. Cloud Comput., 2023, 11(1), 484-498] cannot keep output privacy, due to the simple translation transformation. We also suggest a remedy method by adopting a hybrid transformation which combines the usual translation transformation and resizing transformation so as to protect the output privacy.

Searchable Symmetric Encryption (SSE) has emerged as a promising tool for facilitating efficient query processing over encrypted data stored in un-trusted cloud servers. Several techniques have been adopted to enhance the efficiency and security of SSE schemes. The query processing costs, storage costs and communication costs of any SSE are directly related to the size of the encrypted index that is stored in the server. To our knowledge, there is no work directed towards minimizing the...

We witness an increase in applications like cryptocurrency wallets, which involve users issuing signatures using private keys. To protect these keys from loss or compromise, users commonly outsource them to a custodial server. This creates a new point of failure, because compromise of such a server leaks the user’s key, and if user authentication is implemented with a password then this password becomes open to an offline dictionary attack (ODA). A better solution is to secret-share the key...

Forward-Secure Key-Encapsulation Mechanism (FS-KEM; Canetti et al. Eurocrypt 2003) allows Alice to encapsulate a key $k$ to Bob for some time $t$ such that Bob can decapsulate it at any time $t'\leq t$. Crucially, a corruption of Bob's secret key after time $t$ does not reveal $k$. In this work, we generalize and extend this idea by also taking Post-Compromise Security (PCS) into account and call it Interval Key-Encapsulation Mechanism (IKEM). Thus, we do not only protect confidentiality...

In this work, we consider the setting where one or more users with low computational resources would lie to outsource the task of proof generation for SNARKs to one external entity, named Prover. We study the scenario in which Provers have access to all statements and witnesses to be proven beforehand. We take a different approach to proof aggregation and design a new protocol that reduces simultaneously proving time and communication complexity, without going through recursive proof...

The proliferation of attacks to cloud computing, coupled with the vast amounts of data outsourced to online services, continues to raise major concerns about the privacy for end users. Traditional cryptography can help secure data transmission and storage on cloud servers, but falls short when the already encrypted data needs to be processed by the cloud provider. An emerging solution to this challenge is fully homomorphic encryption (FHE), which enables computations directly on encrypted...

This paper presents a survey of the state-of-the-art pre-silicon security verification techniques for System-on-Chip (SoC) designs, focusing on ensuring that designs, implemented in hardware description languages (HDLs) and synthesized circuits, meet security requirements before fabrication in semiconductor foundries. Due to several factors, pre-silicon security verification has become an essential yet challenging aspect of the SoC hardware lifecycle. The modern SoC design process often...

Anonymity is essential for free speech and expressing dissent, but platform moderators need ways to police bad actors. For anonymous clients, this may involve banning their accounts, docking their reputation, or updating their state in a complex access control scheme. Frequently, these operations happen asynchronously when some violation, e.g., a forum post, is found well after the offending action occurred. Malicious clients, naturally, wish to evade this asynchronous negative feedback....

Anonymous Broadcast Channels (ABCs) allow a group of clients to announce messages without revealing the exact author. Modern ABCs operate in a client-server model, where anonymity depends on some threshold (e.g., 1 of 2) of servers being honest. ABCs are an important application in their own right, e.g., for activism and whistleblowing. Recent work on ABCs (Riposte, Blinder) has focused on minimizing the bandwidth cost to clients and servers when supporting large broadcast channels for such...

Clustering is a crucial unsupervised learning method extensively used in the field of data analysis. For analyzing big data, outsourced computation is an effective solution but privacy concerns arise when involving sensitive information. Fully homomorphic encryption (FHE) enables computations on encrypted data, making it ideal for such scenarios. However, existing privacy-preserving clustering based on FHE are often constrained by the high computational overhead incurred from FHE, typically...

Strike-lists are a common technique for rollback and replay prevention in protocols that require that clients remain anonymous or that their current position in a state machine remain confidential. Strike-lists are heavily used in anonymous credentials, e-cash schemes, and trusted execution environments, and are widely deployed on the web in the form of Privacy Pass (PoPETS '18) and Google Private State Tokens. In such protocols, clients submit pseudorandom tokens associated with each...

Fully homomorphic encryption (FHE) based database outsourcing is drawing growing research interests. At its current state, there exist two primary obstacles against FHE-based encrypted databases (EDBs): i) low data precision, and ii) high computational latency. To tackle the precision-performance dilemma, we introduce ArcEDB, a novel FHE-based SQL evaluation infrastructure that simultaneously achieves high data precision and fast query evaluation. Based on a set of new plaintext encoding...

Oblivious RAM (ORAM) allows a client to securely outsource memory storage to an untrusted server. It has been shown that no ORAM can simultaneously achieve small bandwidth blow-up, small client storage, and a single roundtrip of latency. We consider a weakening of the RAM model, which we call the Single Access Machine (SAM) model. In the SAM model, each memory slot can be written to at most once and read from at most once. We adapt existing tree-based ORAM to obtain an oblivious SAM...

Cryptocurrencies and blockchain technology provide an innovative model for reshaping digital services. Driven by the movement toward Web 3.0, recent systems started to provide distributed services, such as computation outsourcing or file storage, on top of the currency exchange medium. By allowing anyone to join and collect cryptocurrency payments for serving others, these systems create decentralized markets for trading digital resources. Yet, there is still a big gap between the promise of...

Users increasingly store their data in the cloud, thereby benefiting from easy access, sharing, and redundancy. To additionally guarantee security of the outsourced data even against a server compromise, some service providers have started to offer end-to-end encrypted (E2EE) cloud storage. With this cryptographic protection, only legitimate owners can read or modify the data. However, recent attacks on the largest E2EE providers have highlighted the lack of solid foundations for this...

In verifiable outsourcing, an untrusted server runs an expensive computation and produces a succinct proof (called a SNARK) of the results. In many scenarios, the computation accesses a RAM that the server maintains a commitment to (persistent RAM) or that is initially zero (volatile RAM). But, SNARKs for such scenarios are limited by the high overheads associated with existing techniques for RAM checking. We develop new proofs about volatile, persistent, and sparse persistent RAM that...

Collaborative zk-SNARK (USENIX'22) allows multiple parties to jointly create a zk-SNARK proof over distributed secrets (also known as the witness). It provides a promising approach to proof outsourcing, where a client wishes to delegate the tedious task of proof generation to many servers from different locations, while ensuring no corrupted server can learn its witness (USENIX'23). Unfortunately, existing work remains a significant efficiency problem, as the protocols rely heavily on a...

Homomorphic encryption can address key privacy challenges in cloud-based outsourcing by enabling potentially untrusted servers to perform meaningful computation directly on encrypted data. While most homomorphic encryption schemes offer addition and multiplication over ciphertexts natively, any non-linear functions must be implemented as costly polynomial approximations due to this restricted computational model. Nevertheless, the CGGI cryptosystem is capable of performing arbitrary...

Boolean Searchable Symmetric Encryption (SSE) enables secure outsourcing of databases to an untrusted server in encrypted form and allows the client to execute secure Boolean queries involving multiple keywords. The leakage of keyword pair result pattern (KPRP) in a Boolean search poses a significant threat, which reveals the intersection of documents containing any two keywords involved in a search and can be exploited by attackers to recover plaintext information about searched keywords...

The development of cloud computing facilitates data outsourced sharing and storage, but also brings up several security issues. Public key authenticated encryption with keyword search (PAEKS) enables the encrypted search over cloud data while resisting the insider keyword guessing attacks (IKGAs). However, existing PAEKS schemes are limited to a single receiver, restricting application prospects in cloud storage. In addition, quantum computing attacks and key leakage issues further threaten...

Functional Encryption (FE) allows users to extract specific function-related information from encrypted data while preserving the privacy of the underlying plaintext. Though significant research has been devoted to developing secure and efficient Multi-Input Functional Encryption schemes supporting diverse functions, there remains a noticeable research gap in the development of verifiable FE schemes. Functionality and performance have received considerable attention, however, the crucial...

We propose GraphOS, a system that allows a client that owns a graph database to outsource it to an untrusted server for storage and querying. It relies on doubly-oblivious primitives and trusted hardware to achieve a very strong privacy and efficiency notion which we call oblivious graph processing: the server learns nothing besides the number of graph vertexes and edges, and for each query its type and response size. At a technical level, GraphOS stores the graph on a doubly-oblivious data...

Machine-learning systems continue to advance at a rapid pace, demonstrating remarkable utility in various fields and disciplines. As these systems continue to grow in size and complexity, a nascent industry is emerging which aims to bring machine-learning-as-a-service (MLaaS) to market. Outsourcing the operation and training of these systems to powerful hardware carries numerous advantages, but challenges arise when privacy and the correctness of work carried out must be ensured. Recent...

Searchable Symmetric Encryption (SSE) has opened up an attractive avenue for privacy-preserved processing of outsourced data on the untrusted cloud infrastructure. SSE aims to support efficient Boolean query processing with optimal storage and search overhead over large real databases. However, current constructions in the literature lack the support for multi-client search and dynamic updates to the encrypted databases, which are essential requirements for the widespread deployment of SSE...

Oblivious message retrieval (OMR) allows resource-limited recipients to outsource the message retrieval process without revealing which messages are pertinent to which recipient. Its realizations in recent works leave an open problem: can an OMR scheme be both practical and provably secure against spamming attacks from malicious senders (i.e., DoS-resistant) under standard assumptions? In this paper, we first prove that a prior construction $\mathsf{OMRp2}$ is DoS-resistant under a...

SCALES (Small Clients And Larger Ephemeral Servers) model is a recently proposed model for MPC (Acharya et al., TCC 2022). While the SCALES model offers several attractive features for practical large-scale MPC, the result of Acharya et al. only offered semi-honest secure protocols in this model. We present a new efficient SCALES protocol secure against malicious adversaries, for general Boolean circuits. We start with the base construction of Acharya et al. and design and use a suite of...

Anonymous message delivery, as in privacy-preserving blockchain and private messaging applications, needs to protect recipient metadata: eavesdroppers should not be able to link messages to their recipients. This raises the question: how can untrusted servers assist in delivering the pertinent messages to each recipient, without learning which messages are addressed to whom? Recent work constructed Oblivious Message Retrieval (OMR) protocols that outsource the message detection and...

Homomorphic encryption is a powerful privacy-preserving technology that is notoriously difficult to configure and use, even for experts. The key difficulties include restrictive programming models of homomorphic schemes and choosing suitable parameters for an application. In this tutorial, we outline methodologies to solve these issues and allow for conversion of any application to the encrypted domain using both leveled and fully homomorphic encryption. The first approach, called...

Zero-Knowledge Proofs (ZKPs), a cryptographic tool known for decades, have gained significant attention in recent years due to advancements that have made them practically applicable in real-world scenarios. ZKPs can provide unique attributes, such as succinctness, non-interactivity, and the ability to prove knowledge without revealing the information itself, making them an attractive solution for a range of applications. This paper aims to critically analyze the applicability of ZKPs in...

Fully Homomorphic Encryption (FHE) is a prevalent cryptographic primitive that allows for computation on encrypted data. In various cryptographic protocols, this enables outsourcing computation to a third party while retaining the privacy of the inputs to the computation. However, these schemes make an honest-but-curious assumption about the adversary. Previous work has tried to remove this assumption by combining FHE with Verifiable Computation (VC). Recent work has increased the...

The popularity of cloud computing has made outsourced databases prevalent in real-world applications. To protect data security, numerous encrypted outsourced databases have been proposed for this paradigm. However, the maintenance of encrypted databases has scarcely been addressed. In this paper, we focus on a typical maintenance task --- functional dependency (FD) discovery. We develop novel FD protocols in encrypted databases while guaranteeing minimal leakages: nothing is revealed besides...

Homomorphic encryption (HE) enables computation on encrypted data, which in turn facilitates the outsourcing of computation on private data. However, HE offers no guarantee that the returned result was honestly computed by the cloud. In order to have such guarantee, it is necessary to add verifiable computation (VC) into the system. The most efficient recent works in VC over HE focus on verifying operations on the ciphertext space of the HE scheme, which usually lacks the algebraic...

We present two new constructions for private information retrieval (PIR) in the classical setting where the clients do not need to do any preprocessing or store any database dependent information, and the server does not need to store any client-dependent information. Our first construction (HintlessPIR) eliminates the client preprocessing step from the recent LWE-based SimplePIR (Henzinger et. al., USENIX Security 2023) by outsourcing the "hint" related computation to the server,...

When outsourcing a database to an untrusted remote server, one might want to verify the integrity of contents while accessing it. To solve this, Blum et al. [FOCS `91] propose the notion of memory checking. Memory checking allows a user to run a RAM program on a remote server, with the ability to verify integrity of the storage with small local storage. In this work, we define and initiate the formal study of memory checking for Parallel RAMs (PRAMs). The parallel RAM...

Computing the distance between two non-normalized vectors $\mathbfit{x}$ and $\mathbfit{y}$, represented by $\Delta(\mathbfit{x},\mathbfit{y})$ and comparing it to a predefined public threshold $\tau$ is an essential functionality used in privacy-sensitive applications such as biometric authentication, identification, machine learning algorithms ({\em e.g.,} linear regression, k-nearest neighbors, etc.), and typo-tolerant password-based authentication. Tackling a widely used distance...

Homomorphic Encryption (HE) is one of the mainstream cryptographic tools used to enable secure outsourced computation. A typical task is secure matrix computation. Popular HE schemes are all based on the problem of Ring Learning with Errors (RLWE), where the messages are encrypted in a ring. In general, the ring dimension should be large to ensure security, which is often larger than the matrix size. Hence, exploiting the ring structure to make fast homomorphic matrix computation has been an...

Domain Generation Algorithms (DGAs) are used by malware to generate pseudorandom domain names to establish communication between infected bots and Command and Control servers. While DGAs can be detected by machine learning (ML) models with great accuracy, offering DGA detection as a service raises privacy concerns when requiring network administrators to disclose their DNS traffic to the service provider. We propose the first end-to-end framework for privacy-preserving classification as a...

We study verifiable outsourcing of computation in a model where the verifier has black-box access to the function being computed. We introduce the problem of oracle-aided batch verification of computation (OBVC) for a function class $\mathcal{F}$. This allows a verifier to efficiently verify the correctness of any $f \in \mathcal{F}$ evaluated on a batch of $n$ instances $x_1, \ldots, x_n$, while only making $\lambda$ calls to an oracle for $f$ (along with $O(n \lambda)$ calls to...

As concerns are increasingly raised about data privacy, encrypted database management system (DBMS) based on fully homomorphic encryption (FHE) attracts increasing research attention, as FHE permits DBMS to be directly outsourced to cloud servers without revealing any plaintext data. However, the real-world deployment of FHE-based DBMS faces two main challenges: i) high computational latency, and ii) lack of elastic query processing capability, both of which stem from the inherent...

As cloud computing continues to gain widespread adoption, safeguarding the confidentiality of data entrusted to third-party cloud service providers becomes a critical concern. While traditional encryption methods offer protection for data at rest and in transit, they fall short when it comes to where it matters the most, i.e., during data processing. To address this limitation, we present HELM, a framework for privacy-preserving data processing using homomorphic encryption. HELM...

Privacy-Preserving Machine Learning (PPML) provides protocols for learning and statistical analysis of data that may be distributed amongst multiple data owners (e.g., hospitals that own proprietary healthcare data), while preserving data privacy. The PPML literature includes protocols for various learning methods, including ridge regression. Ridge regression controls the $L_2$ norm of the model, but does not aim to strictly reduce the number of non-zero coefficients, namely the $L_0$ norm...

Cryptographic proof systems provide integrity, fairness, and privacy in applications that outsource data processing tasks. However, general-purpose proof systems do not scale well to large inputs. At the same time, ad-hoc solutions for concrete applications - e.g., machine learning or image processing - are more efficient but lack modularity, hence they are hard to extend or to compose with other tools of a data-processing pipeline. In this paper, we combine the performance of tailored...

Emails have improved our workplace efficiency and communication. However, they are often processed unencrypted by mail servers, leaving them open to data breaches on a single service provider. Public-key based solutions for end-to-end secured email, such as Pretty Good Privacy (PGP) and Secure/Multipurpose Internet Mail Extensions (S/MIME), are available but are not widely adopted due to usability obstacles and also hinder processing of encrypted emails. We propose PrivMail, a novel...

Distributed key management (DKM) services are multi-party services that allow their users to outsource the generation, storage, and usage of cryptographic private keys, while guaranteeing that none of the involved service providers learn the private keys in the clear. This is typically achieved through distributed key generation (DKG) protocols, where the service providers generate the keys on behalf of the users in an interactive protocol, and each of the servers stores a share of each key...

Digital Covid certificates are the first widely deployed end-user cryptographic certificates. For service providers, such as airlines or event ticket vendors, that needed to check that their (global) customers satisfy certain health policies, the verification of such Covid certificates was challenging though - not because of the cryptography involved, but due to the multitude of issuers, different certificate types and the evolving nature of country-specific policies that had to be...

In oblivious finite automata evaluation, one party holds a private automaton, and the other party holds a private string of characters. The objective is to let the parties know whether the string is accepted by the automaton or not, while keeping their inputs secret. The applications include DNA searching, pattern matching, and more. Most of the previous works are based on asymmetric cryptographic primitives, such as homomorphic encryption and oblivious transfer. These primitives are...

Secret sharing is a cryptographic primitive that divides a secret into several shares, and allows only some combinations of shares to recover the secret. As it can also be used in secure multi-party computation protocol with outsourcing servers, several variations of secret sharing are devised for this purpose. Most of the existing protocols require the number of computing servers to be determined in advance. However, in some situations we may want the system to be "evolving". We may want to...

This paper proposes $t$-secure homomorphic secret sharing schemes for low degree polynomials. Homomorphic secret sharing is a cryptographic technique to outsource the computation to a set of servers while restricting some subsets of servers from learning the secret inputs. Prior to our work, at Asiacrypt 2018, Lai, Malavolta, and Schröder proposed a $1$-secure scheme for computing polynomial functions. They also alluded to $t$-secure schemes without giving explicit constructions;...

Private payments in blockchain-based cryptocurrencies have been a topic of research, both academic and industrial, ever since the advent of Bitcoin. Stealth address payments were proposed as a solution to improve payment privacy for users and are, in fact, deployed in several major cryptocurrencies today. The mechanism lets users receive payments so that none of these payments are linkable to each other or the recipient. Currently known stealth address mechanisms either (1) are insecure in...

In public key encryption (PKE), anonymity is essential to ensure privacy by preventing the ciphertext from revealing the recipient’s identity. However, the literature has addressed the anonymity of PKE under different attack scenarios to a limited extent. Benhamouda et al. (TCC 2020) introduced the first formal definition of anonymity for PKE under corruption, and Huang et al. (ASIACRYPT 2022) made further extensions and provided a generic framework. In this paper, we introduce a new...

Vehicular Social Networks (VSNs) rely on data shared by users to provide convenient services. Data is outsourced to the cloud server and the distributed roadside unit in VSNs. However, roadside unit has limited resources, so that data sharing process is inefficient and is vulnerable to security threats, such as illegal access, tampering attack and collusion attack. In this article, to overcome the shortcomings of security, we define a chain tolerance semi-trusted model to describe the...

$\newcommand{\gen}{\mathsf{Gen}}\newcommand{\enc}{\mathsf{Enc}}\newcommand{\dec}{\mathsf{Dec}}$ A recent work of Fleischhacker, Larsen, and Simkin (Eurocrypt 2023) shows how to efficiently compress encrypted sparse vectors. Subsequently, Fleischhacker, Larsen, Obremski, and Simkin (Eprint 2023) improve upon their work and provide more efficient constructions solving the same problem. Being able to efficiently compress such vectors is very useful in a variety of applications, such as...

A decade of active research has led to practical constructions of zero-knowledge succinct non-interactive arguments of knowledge (zk-SNARKs) that are now being used in a wide variety of applications. Despite this astonishing progress, overheads in proof generation time remain significant. In this work, we envision a world where consumers with low computational resources can outsource the task of proof generation to a group of untrusted servers in a privacy-preserving manner. The main...

In this paper, we study oblivious key-value stores (OKVS) that enable encoding n key-value pairs into length $m$ encodings while hiding the input keys. The goal is to obtain high rate, $n/m$, with efficient encoding and decoding algorithms. We present $\mathsf{RB\text{-}OKVS}$ built on random band matrices that obtains near-optimal rates as high as 0.97 whereas prior works could only achieve rates up to 0.81 with similar encoding times. Using $\mathsf{RB\text{-}OKVS}$, we obtain...

Searchable Symmetric Encryption (SSE) supports efficient keyword searches over encrypted outsourced document collections while minimizing information leakage. All practically efficient SSE schemes supporting conjunctive queries rely crucially on quantum-broken cryptographic assumptions (such as discrete-log hard groups) to achieve compact storage and fast query processing. On the other hand, quantum-safe SSE schemes based on purely symmetric-key crypto-primitives either do not support...

Oblivious RAMs (ORAMs) are an important cryptographic primitive that enable outsourcing data to a potentially untrusted server while hiding patterns of access to the data. ORAMs provide strong guarantees even in the face of a {\em persistent adversary} that views the transcripts of all operations and resulting memory contents. Unfortunately, the strong guarantees against persistent adversaries comes at the cost of efficiency as ORAMs are known to require $\Omega(\log n)$ overhead. In an...

Fully Homomorphic Encryption (FHE) enables computations to be performed on encrypted data, so one can outsource computations of confidential information to an untrusted party. Ironically, FHE requires the client to generate massive evaluation keys and transfer them to the server side where all computations are supposed to be performed. In this paper, we propose LFHE, the Light-key FHE variant of the FHEW scheme introduced by Ducas and Micciancio in Eurocrypt 2015, and its improvement TFHE...

Searchable encrypted systems enable privacy-preserving keyword search on encrypted data. Symmetric systems achieve high efficiency (e.g., sublinear search), but they mostly support single-user search. Although systems based on public-key or hybrid models support multi-user search, they incur inherent security weaknesses (e.g., keyword-guessing vulnerabilities) and scalability limitations due to costly public-key operations (e.g., pairing). More importantly, most encrypted search designs leak...

Homomorphic Encryption (HE) is a type of cryptography that allows computing on encrypted data, enabling computation on sensitive data to be outsourced securely. Many popular HE schemes rely on noise for their security. On the other hand, Differential Privacy seeks to guarantee the privacy of data subjects by obscuring any one individual's contribution to an output. Many mechanisms for achieving Differential Privacy involve adding appropriate noise. In this work, we investigate the extent to...

Encrypted computation allows a client to securely outsource the storage and processing of sensitive private data to an untrusted third party cloud server. Fully Homomorphic Encryption (FHE) and Garbled Circuit (GC) are state-of-the-art general-purpose primitives that support encrypted computation. FHE enables arbitrary encrypted computation ensuring data-privacy but suffers from huge computation overhead and poor scalability. GC additionally provides function privacy, but is often not...

Distributed integrated circuit (IC) supply chain has resulted in a myriad of security vulnerabilities including that of hardware Trojan (HT). An HT can perform malicious modifications on an IC design with potentially disastrous consequences, such as leaking secret information in cryptographic applications or altering operation instructions in processors. Due to the emergence of outsourced fabrication, an untrusted foundry is considered the most potent adversary in introducing an HT. This can...

Private messaging systems that use a bulletin board, like privacy-preserving blockchains, have been a popular topic during the last couple of years. In these systems, typically a private message is posted on the board for a recipient and the privacy requirement is that no one can determine the sender and the recipient of the message. Until recently, the efficiency of these recipients was not considered, and the party had to perform a naive scan of the board to retrieve their messages. ...

Anonymous message delivery, as in private communication and privacy-preserving blockchain applications, ought to protect recipient metadata: a message should not be inadvertently linkable to its destination. But how can messages then be delivered to each recipient, without each recipient scanning all messages? Recent work constructed Oblivious Message Retrieval (OMR) protocols that outsource this job to untrusted servers in a privacy-preserving manner. We consider the case of group...

Proof of Storage-time (PoSt) is a cryptographic primitive that enables a server to demonstrate non-interactive continuous avail- ability of outsourced data in a publicly verifiable way. This notion was first introduced by Filecoin to secure their Blockchain-based decentral- ized storage marketplace, using expensive SNARKs to compact proofs. Recent work [2] employs the notion of trapdoor delay function to address the problem of compact PoSt without SNARKs. This approach however entails...

Tremendous efforts have been made to improve the efficiency of secure Multi-Party Computation (MPC), which allows n ≥ 2 parties to jointly evaluate a target function without leaking their own private inputs. It has been confirmed by previous research that Three-Party Computation (3PC) and outsourcing computations to GPUs can lead to huge performance improvement of MPC in computationally intensive tasks such as Privacy-Preserving Machine Learning (PPML). A natural question to ask is whether...

Fully homomorphic encryption FHE has been one of the most promising cryptographic tools for secure two-party computation and secure outsourcing computation in recent years. However, the complex bootstrapping procedure in FHE schemes is the main bottleneck of it practical usage, and the TFHE scheme is the state-of-the-art for efficient bootstrapping. To further improve the efficiency of bootstrapping in TFHE, the number of fast Fourier transforms (FFT) should be reduced since bootstrapping...

Electronic Medical Records (EMRs) have been utilized in plentiful medical institutions due to their superior convenience and low storage overhead. Nevertheless, it is difficult for medical departments with disparate management regulations to share EMRs through secure communication channels since sensitive EMRs are prone to be tampered with. Therefore, the EMRs should be encrypted before being outsourced to the network servers. Public key Encryption with Keyword Search (PEKS) has the ability...

Data outsourcing is a solution aimed at addressing the security and reliability issues of data storage by ensuring professional handling of the data. The growing use of outsourcing is causing concern among users due to the lack of assurance regarding the security and reliability of data stored on servers. To address these issues, some attempts have been made to implement Secret Sharing-based Data Outsourcing (SSDO) schemes. The low efficiency of these schemes led researchers to use an index...

Oblivious RAM (ORAM) allows a client to outsource storage to a remote server while hiding the data access pattern from the server. Many ORAM designs have been proposed to reduce the computational overhead and bandwidth blowup for the client. A recent work, Onion Ring ORAM (CCS'19), is able to achieve $O(1)$ bandwidth blowup in the online phase using fully homomorphic encryption (FHE) techniques, at the cost of a computationally expensive client-side offline phase. Furthermore, such a scheme...

The production of modern integrated circuit (IC) requires a complex, outsourced supply chain involving computer-aided design (CAD) tools, expert knowledge, and advanced foundries. This complexity has led to various security threats, such as Trojans inserted by adversaries during outsourcing, and physical probing or manipulation of devices at run-time. Our proposed solution, DEFense is an extensible CAD framework for evaluating and proactively mitigating threats to IC at the design-time...

Dynamic Symmetric Searchable Encryption (SSE) enables a user to outsource the storage of an encrypted database to an untrusted server, while retaining the ability to privately search and update the outsourced database. The performance bottleneck of SSE schemes typically comes from their I/O efficiency. Over the last few years, a line of work has substantially improved that bottleneck. However, all existing I/O-efficient SSE schemes have a common limitation: they are not forward-secure. Since...

This paper proposes Prism, Private Verifiable Set Computation over Multi-Owner Outsourced Databases, a secret sharing based approach to compute private set operations (i.e., intersection and union), as well as aggregates over outsourced databases belonging to multiple owners. Prism enables data owners to pre-load the data onto non-colluding servers and exploits the additive and multiplicative properties of secret-shares to compute the above-listed operations in (at most) two rounds of...

Homomorphic encryption (HE) allows for computations over ciphertexts while they are encrypted. Because of this, HE supports the outsourcing of computation on private data. Due to the additional risks caused by data outsourcing, the ability to recover from losses is essential, but doing so on data encrypted under an HE scheme introduces additional challenges for recovery and usability. This work introduces X-Cipher, which aims to make HE ciphertexts resilient by ensuring they are private and...

We initiate a formal study of individual cryptography. Informally speaking, an algorithm $\mathsf{Alg}$ is "individual" if, in every implementation of $\mathsf{Alg}$, there always exists an individual user with full knowledge of the cryptographic data $S$ used by $\mathsf{Alg}$. In particular, it should be infeasible to design implementations of this algorithm that would hide $S$ by distributing it between a group of parties using an MPC protocol or outsourcing it to a trusted execution...

We propose a single-tiered hybrid Proof-of-Work consensus protocol to encourage decentralization in bitcoin. Our new mechanism comprises coupled puzzles of which properties differ from each other; the one is the extant outsourceable bitcoin puzzle while the other is non-outsourceable. Our new protocol enables miners to solve either puzzle as they want; therefore, blocks can be generated by either puzzle. Our hybrid consensus can be successfully implemented in bitcoin, because it is...

The redundant of multimedia data made an unnecessary waste in encrypted cloud storage, unlike text with completely consistent content, multimedia data allows a certain degree of similarity in deduplication, In this work, we focus on the multimedia data which takes a seriously proportion of storage in scenarios such as data outsourcing to propose secure fuzzy deduplication without the additional servers based on Convergent Encryption(CE), say the Single-server Fuzzy Deduplication (SSFD)....

Secure cryptographic storage is one of the most important issues that both businesses and end-users take into account before moving their data to either centralized clouds or blockchain-based decen- tralized storage marketplace. Recent work [4 ] formalizes the notion of Proof of Storage-Time (PoSt) which enables storage servers to demonstrate non-interactive continuous availability of outsourced data in a publicly verifiable way. The work also proposes a stateful compact PoSt...

Verifying the absence of maliciously inserted Trojans in ICs is a crucial task – especially for security-enabled products. Depending on the concrete threat model, different techniques can be applied for this purpose. Assuming that the original IC layout is benign and free of backdoors, the primary security threats are usually identified as the outsourced manufacturing and transportation. To ensure the absence of Trojans in commissioned chips, one straightforward solution is to compare the...

As digital tokens on blockchains such as non-fungible tokens (NFTs) increase in popularity and scale, the existing interfaces (ERC-721, ERC-20, and many more) are being exposed for being expensive and not scalable. As a result, tokens are being forced to be implemented on alternative blockchains where it is cheaper but less secure. To offer a solution without making security tradeoffs, we propose using joint cryptographic accumulators (e.g. joint Merkle trees). We propose a method of...

There has been intense interest over the last decade in implementations of _probabilistic proofs_ (IPs, SNARKs, PCPs, and so on): protocols in which an untrusted party proves to a verifier that a given computation was executed properly, possibly in zero knowledge. Nevertheless, implementations still do not scale beyond small computations. A central source of overhead is the _front-end_: translating from the abstract computation to a set of equivalent arithmetic constraints. This paper...

Storage-as-a-service (STaaS) permits the client to outsource her data to the cloud thereby, reducing data management and maintenance costs. However, STaaS also brings significant data integrity and soundness concerns since the storage provider might not keep the client data intact and retrievable all the time (e.g., cost saving via deletions). Proof of Retrievability (PoR) can validate the integrity and retrievability of remote data effectively. This technique can be useful for regular...

We study the task of obliviously compressing a vector comprised of $n$ ciphertexts of size $\xi$ bits each, where at most $t$ of the corresponding plaintexts are non-zero. This problem commonly features in applications involving encrypted outsourced storages, such as searchable encryption or oblivious message retrieval. We present two new algorithms with provable worst-case guarantees, solving this problem by using only homomorphic additions and multiplications by constants. Both of our...