Authentication often bridges real-world individuals and their virtual public identities, like usernames, user IDs and e-mails, exposing vulnerabilities that threaten user privacy. This research introduces COCO (Coconuts and Oblivious Computations for Orthogonal Authentication), a framework that segregates roles among Verifiers, Authenticators, and Clients to achieve privacy-preserving authentication. COCO eliminates the need for Authenticators to directly access virtual public identifiers...

Anonymous digital credentials allow a user to prove possession of an attribute that has been asserted by an identity issuer without revealing any extra information about themselves. For example, a user who has received a digital passport credential can prove their “age is $>18$” without revealing any other attributes such as their name or date of birth. Despite inherent value for privacy-preserving authentication, anonymous credential schemes have been difficult to deploy at scale. ...

The fast-paced development and deployment of private messaging applications demands mechanisms to protect against the concomitant potential for abuse. While widely used end-to-end encrypted (E2EE) messaging systems have deployed mechanisms for users to verifiably report abusive messages without compromising the privacy of unreported messages, abuse reporting schemes for systems that additionally protect message metadata are still in their infancy. Existing solutions either focus on a...

Ensuring transaction privacy in blockchain systems is essential to safeguard user data and financial activity from exposure on public ledgers. This paper conducts a systematization of knowledge (SoK) on privacy-preserving techniques in cryptocurrencies with native privacy features. We define and compare privacy notions such as confidentiality, k-anonymity, full anonymity, and sender-receiver unlinkability, and categorize the cryptographic techniques employed to achieve these guarantees. Our...

A group signatures allows a user to sign a message anonymously on behalf of a group and provides accountability by using an opening authority who can ``open'' a signature and reveal the signer's identity. Group signatures have been widely used in privacy-preserving applications including anonymous attestation and anonymous authentication. Fully dynamic group signatures allow new members to join the group and existing members to be revoked if needed. Symmetric-key based group signature...

This article proposes an extension for privacy-preserving applications to introduce sanctions or prohibition lists. When initiating a particular action, the user can prove, in addition to the application logic, that they are not part of the sanctions lists (one or more) without compromising sensitive data. We will show how this solution can be integrated into applications, using the example of extending Freedom Tool (a voting solution based on biometric passports). We will also consider ways...

In the digital age, the concept of consent for online actions executed by third parties is crucial for maintaining trust and security in third-party services. This work introduces the notion of cryptographically secure digital consent, which aims to replicate the traditional consent process in the online world. We provide a flexible digital consent solution that accommodates different use cases and ensures the integrity of the consent process. The proposed framework involves a client...

Quantum information allows us to build quantum money schemes, where a bank can issue banknotes in the form of authenticatable quantum states that cannot be cloned or counterfeited: a user in possession of k banknotes cannot produce k +1 banknotes. Similar to paper banknotes, in existing quantum money schemes, a banknote consists of an unclonable quantum state and a classical serial number, signed by bank. Thus, they lack one of the most fundamental properties cryptographers look for in a...

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

Large language models (LLMs) have recently transformed many industries, enhancing content generation, customer service agents, data analysis and even software generation. These applications are often hosted on remote servers to protect the neural-network model IP; however, this raises concerns about the privacy of input queries. Fully Homomorphic Encryption (FHE), an encryption technique that allows for computations on private data, has been proposed as a solution to the challenge....

Zero-knowledge for set membership is a building block at the core of several privacy-aware applications, such as anonymous payments, credentials and whitelists. We propose a new efficient construction for the batching variant of the problem, where a user intends to show knowledge of several elements (a batch) in a set without any leakage on the elements. Our construction is transparent—it does not requires a trusted setup—and based on Curve Trees by Campanelli, Hall-Andersen and Kamp...

Many messaging platforms have integrated end-to-end (E2E) encryption into their services. This widespread adoption of E2E encryption has triggered a technical tension between user privacy and illegal content moderation. The existing solutions either support only unframeability or deniability, or they are prone to abuse (the moderator can perform content moderation for all messages, whether illegal or not), or they lack mechanisms for retrospective content moderation. To address the above...

In modern business to customer interactions, handling private or confidential data is essential. Private Function Evaluation (PFE) protocols ensure the privacy of both the customers' input data and the business' function evaluated on it which is often sensitive intellectual property (IP). However, fully hiding the function in PFE results in high performance overhead. Semi-Private Function Evaluation (SPFE) is a generalization of PFE to only partially hide the function, whereas specific...

Encrypted Search Algorithms (ESAs) are a technique to encrypt data while the user can still search over it. ESAs can protect privacy and ensure security of sensitive data stored on a remote storage. Originally, ESAs were used in the context of documents that consist of keywords. The user encrypts the documents, sends them to a remote server and is still able to search for keywords, without exposing information about the plaintext. The idea of ESAs has also been applied to relational...

Peer-to-peer communication systems can provide many functions, including anonymized routing of network traffic, massive parallel computing environments, and distributed storage. Anonymity refers to the state of being completely nameless, with no attached identifiers. Pseudonymity involves the use of a fictitious name that can be consistently linked to a particular user, though not necessarily to the real identity. Both provide a layer of privacy, shielding the user's true identity from...

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...

Modern data analytics requires computing functions on streams of data points from many users that are challenging to calculate, due to both the high scale and nontrivial nature of the computation at hand. The need for data privacy complicates this matter further, as general-purpose privacy-enhancing technologies face limitations in at least scalability or utility. Existing work has attempted to improve this by designing purpose-built protocols for the use case of Private Stream Aggregation;...

We introduce Compass, a semantic search system over encrypted data that offers high accuracy, comparable to state-of-the-art plaintext search algorithms while protecting data, queries and search results from a fully compromised server. Additionally, Compass enables privacy-preserving RAG where both the RAG database and the query are protected. Compass contributes a novel way to traverse the Hierarchical Navigable Small Worlds (HNSW) graph, a top-performing nearest neighbor search index, over...

Delegatable anonymous credentials (DACs) enable a root issuer to delegate credential-issuing power, allowing a delegatee to take a delegator role. To preserve privacy, credential recipients and verifiers should not learn anything about intermediate issuers in the delegation chain. One particularly efficient approach to constructing DACs is due to Crites and Lysyanskaya (CT-RSA '19). In contrast to previous approaches, it is based on mercurial signatures (a type of equivalence-class...

We propose AQQUA: a digital payment system that combines auditability and privacy. AQQUA extends Quisquis by adding two authorities; one for registration and one for auditing. These authorities do not intervene in the everyday transaction processing; as a consequence, the decentralized nature of the cryptocurrency is not disturbed. Our construction is account-based. An account consists of an updatable public key which functions as a cryptographically unlinkable pseudonym, and of commitments...

Recent advancements in transformers have revolutionized machine learning, forming the core of Large language models (LLMs). However, integrating these systems into everyday applications raises privacy concerns as client queries are exposed to model owners. Secure multiparty computation (MPC) allows parties to evaluate machine learning applications while keeping sensitive user inputs and proprietary models private. Due to inherent MPC costs, recent works introduce model-specific optimizations...

Single Sign-On (SSO) allows users to conveniently authenticate to many Relying Parties (RPs) through a central Identity Provider (IdP). SSO supports unlinkable authentication towards the RPs via pairwise pseudonyms, where the IdP assigns the user an RP-specific pseudonym. This feature has been rolled out prominently within Apple's SSO service. While establishing unlinkable identities provides privacy towards RPs, it actually emphasizes the main privacy problem of SSO: with every...

Cryptographic wallets are an essential tool in Blockchain networks to ensure the secure storage and maintenance of an user's cryptographic keys. Broadly, wallets can be divided into three categories, namely custodial, non-custodial, and shared-custodial wallets. The first two are centralized solutions, i.e., the wallet is operated by a single entity, which inherently introduces a single point of failure. Shared-custodial wallets, on the other hand, are maintained by two independent parties,...

As large language models (LLMs) continue to gain popularity, concerns about user privacy are amplified, given that the data submitted by users for inference may contain sensitive information. Therefore, running LLMs through secure two-party computation (a.k.a. secure LLM inference) has emerged as a prominent topic. However, many operations in LLMs, such as Softmax and GELU, cannot be computed using conventional gates in secure computation; instead, lookup tables (LUTs) have to be utilized,...

Privacy is a major concern in large-scale digital applications, such as cloud-computing, machine learning services, and access control. Users want to protect not only their plain data but also their associated attributes (e.g., age, location, etc). Functional encryption (FE) is a cryptographic tool that allows fine-grained access control over encrypted data. However, existing FE fall short as they are either inefficient and far from reality or they leak sensitive user-specific...

Self-sovereign identity (SSI) systems empower users to (anonymously) establish and verify their identity when accessing both digital and real-world resources, emerging as a promising privacy-preserving solution for user-centric identity management. Recent work by Maram et al. proposes the privacy-preserving Sybil-resistant decentralized SSI system CanDID (IEEE S&P 2021). While this is an important step, notable shortcomings undermine its efficacy. The two most significant among them being...

This Systematization of Knowledge conducts a survey of contemporary distributed blockchain protocols, with the aim of identifying cryptographic and design techniques which practically enable both expressive programmability and user data confidentiality. To facilitate a framing which supports the comparison of concretely very different protocols, we define an epoch-based computational model in the form of a flexible UC-style ideal functionality which divides the operation of...

This paper presents a new architecture for metadata-private messaging that counters scalability challenges by offloading most computations to the clients. At the core of our design is a distributed private information retrieval (PIR) protocol, where the responder delegates its work to alleviate PIR's computational bottleneck and catches misbehaving delegates by efficiently verifying their results. We introduce DPIR, a messaging system that uses distributed PIR to let a server storing...

Internet of Medical Things (IoMT) has gained significant research focus in both academic and medical institutions. Nevertheless, the sensitive data involved in IoMT raises concerns regarding user validation and data privacy. To address these concerns, certificateless signcryption (CLSC) has emerged as a promising solution, offering authenticity, confidentiality, and unforgeability. Unfortunately, most existing CLSC schemes are impractical for IoMT due to their heavy computational and storage...

If a web service is so secure that it does not even know—and does not want to know—the identity and contact info of its users, can it still offer account recovery if a user forgets their password? This paper is the culmination of the authors' work to design a cryptographic protocol for account recovery for use by a prominent secure matching system: a web-based service that allows survivors of sexual misconduct to become aware of other survivors harmed by the same perpetrator. In such a...

End-to-End (E2E) encrypted messaging, which prevents even the service provider from learning communication contents, is gaining popularity. Since users care about maintaining access to their data even if their devices are lost or broken or just replaced, these systems are often paired with cloud backup solutions: Typically, the user will encrypt their messages with a fixed key, and upload the ciphertexts to the server. Unfortunately, this naive solution has many drawbacks. First, it often...

Decentralized payments have evolved from using pseudonymous identifiers to much more elaborate mechanisms to ensure privacy. They can shield the amounts in payments and achieve untraceability, e.g., decoy-based untraceable payments use decoys to obfuscate the actual asset sender or asset receiver. There are two types of decoy-based payments: full decoy set payments that use all other available users as decoys, e.g., Zerocoin, Zerocash, and ZCash, and user-defined decoy set payments where...

Ring signatures, a cryptographic primitive introduced by Rivest, Shamir and Tauman (ASIACRYPT 2001), offer signer anonymity within dynamically formed user groups. Recent advancements have focused on lattice-based constructions to improve efficiency, particularly for large signing rings. However, current state-of-the-art solutions suffer from significant overhead, especially for smaller rings. In this work, we present a novel NTRU-based ring signature scheme, Gandalf, tailored towards...

End-to-end encrypted messaging applications ensure that an attacker cannot read a user's message history without their decryption keys. While this provides strong privacy, it creates a usability problem: if a user loses their devices and cannot access their decryption keys, they can no longer access their account. To solve this usability problem, users should be able to back up their account information with the messaging provider. For privacy, this backup should be encrypted and the...

In many real-world scenarios, there are cases where a client wishes to check if a data element they hold is included in a set segmented across a large number of data holders. To protect user privacy, the client’s query and the data holders’ sets should remain encrypted throughout the whole process. Prior work on Private Set Intersection (PSI), Multi-Party PSI (MPSI), Private Membership Test (PMT), and Oblivious RAM (ORAM) falls short in this scenario in many ways. They either require...

Secret sharing allows a user to split a secret into many shares so that the secret can be recovered if, and only if, an authorized set of shares is collected. Although secret sharing typically does not require any computational hardness assumptions, its security does require that an adversary cannot collect an authorized set of shares. Over long periods of time where an adversary can benefit from multiple data breaches, this may become an unrealistic assumption. We initiate the...

We present a framework for privacy-preserving streaming algorithms which combine the memory-efficiency of streaming algorithms with strong privacy guarantees. These algorithms enable some number of servers to compute aggregate statistics efficiently on large quantities of user data without learning the user's inputs. While there exists limited prior work that fits within our model, our work is the first to formally define a general framework, interpret existing methods within this general...

With additively homomorphic encryption (AHE), one can compute, from input ciphertexts $\mathsf{Enc}(x_1),\ldots,\mathsf{Enc}(x_n)$, and additional inputs $y_1,\ldots,y_k$, a ciphertext $c_\textit{f}=\mathsf{Enc}(f(x_1,\ldots,x_n,y_1,\ldots, y_k))$ for any polynomial $f$ in which each monomial has total degree at most $1$ in the $x$-variables (but can be arbitrary in the $y$-variables). For AHE that satisfies a set of natural requirements, we give a non-interactive zero-knowledge proof...

With the rising popularity of DeFi applications it is important to implement protections for regular users of these DeFi platforms against large parties with massive amounts of resources allowing them to engage in market manipulation strategies such as frontrunning/backrunning. Moreover, there are many situations (such as recovery of funds from vulnerable smart contracts) where a user may not want to reveal their transaction until it has been executed. As such, it is clear that preserving...

We present Whisper, a system for privacy-preserving collection of aggregate statistics. Like prior systems, a Whisper deployment consists of a small set of non-colluding servers; these servers compute aggregate statistics over data from a large number of users without learning the data of any individual user. Whisper’s main contribution is that its server- to-server communication cost and its server-side storage costs scale sublinearly with the total number of users. In particular, prior...

Existing oblivious systems offer robust security by concealing memory access patterns, but they encounter significant scalability and performance challenges. Recent efforts to enhance the practicality of these systems involve embedding oblivious computation, e.g., oblivious sorting and shuffling, within Trusted Execution Environments (TEEs). For instance, oblivious sort has been heavily utilized: in Oblix (S&P'18), when oblivious indexes are created and accessed; in Snoopy's high-throughput...

Machine learning as a service requires the client to trust the server and provide its own private information to use this service. Usually, clients may worry that their private data is being collected by server without effective supervision, and the server also aims to ensure proper management of the user data to foster the advancement of its services. In this work, we focus on private decision tree evaluation (PDTE) which can alleviates such privacy concerns associated with classification...

Fully homomorphic encryption (FHE) allows for evaluating arbitrary functions over encrypted data. In Multi-party FHE applications, different parties encrypt their secret data and submit ciphertexts to a server, which, according to the application logic, performs homomorphic operations on them. For example, in a secret voting application, the tally is computed by summing up the ciphertexts encoding the votes. Valid encrypted votes are of the form $E(0)$ and $E(1)$. A malicious voter could...

Transformer neural networks have gained significant traction since their introduction, becoming pivotal across diverse domains. Particularly in large language models like Claude and ChatGPT, the transformer architecture has demonstrated remarkable efficacy. This paper provides a concise overview of transformer neural networks and delves into their security considerations, focusing on covert channel attacks and their implications for the safety of large language models. We present a covert...

Analyzing user data while protecting the privacy of individuals remains a big challenge. Trusted execution environments (TEEs) are a possible solution as they protect processes and Virtual Machines (VMs) against malicious hosts. However, TEEs can leak access patterns to code and to the data being processed. Furthermore, when data is stored in a TEE database, the data volume required to answer a query is another unwanted side channel that contains sensitive information. Both types of...

Biometric authentication eliminates the need for users to remember secrets and serves as a convenient mechanism for user authentication. Traditional implementations of biometric-based authentication store sensitive user biometry on the server and the server becomes an attractive target of attack and a source of large-scale unintended disclosure of biometric data. To mitigate the problem, we can resort to privacy-preserving computation and store only protected biometrics on the server. While...

In [1], two generic constructions for biometric-based non-transferable Attribute Based Credentials (biometric ABC) are presented, which offer different trade-offs between efficiency and trust assumptions. In this paper, we focus on the second scheme denoted as BioABC-ZK that tries to remove the strong (and unrealistic) trust assumption on the Reader R, and show that BioABC-ZK has a security flaw for a colluding R and Verifier V. Besides, BioABC-ZK lacks GDPR-compliance, which requires secure...

In federated learning, secure aggregation (SA) protocols like Flamingo (S\&P'23) and LERNA (ASIACRYPT'23) have achieved efficient multi-round SA in the malicious model. However, each round of their aggregation requires at least three client-server round-trip communications and lacks support for aggregation result verification. Verifiable SA schemes, such as VerSA (TDSC'21) and Eltaras et al.(TIFS'23), provide verifiable aggregation results under the security assumption that the server does...

To resist the regimes of ubiquitous surveillance imposed upon us in every facet of modern life, we need technological tools that subvert surveillance systems. Unfortunately, while cryptographic tools frequently demonstrate how we can construct systems that safeguard user privacy, there is limited motivation for corporate entities engaged in surveillance to adopt these tools, as they often clash with profit incentives. This paper demonstrates how, in one particular aspect of everyday life --...

Classifying images has become a straightforward and accessible task, thanks to the advent of Deep Neural Networks. Nevertheless, not much attention is given to the privacy concerns associated with sensitive data contained in images. In this study, we propose a solution to this issue by exploring an intersection between Machine Learning and cryptography. In particular, Fully Homomorphic Encryption (FHE) emerges as a promising solution, as it enables computations to be performed on encrypted...

Private messaging platforms provide strong protection against platform eavesdropping, but malicious users can use privacy as cover for spreading abuse and misinformation. In an attempt to identify the sources of misinformation on private platforms, researchers have proposed mechanisms to trace back the source of a user-reported message (CCS '19,'21). Unfortunately, the threat model considered by initial proposals allowed a single user to compromise the privacy of another user whose...

An Oblivious Pseudo-Random Function (OPRF) is a two-party protocol for jointly evaluating a Pseudo-Random Function (PRF), where a user has an input x and a server has an input k. At the end of the protocol, the user learns the evaluation of the PRF using key k at the value x, while the server learns nothing about the user's input or output. OPRFs are a prime tool for building secure authentication and key exchange from passwords, private set intersection, private information retrieval,...

Confidentiality and authentication are two main security goals in secure electronic mail (e-mail). Furthermore, deniability is also a significant security property for some e-mail applications to protect the privacy of the sender. Although searchable encryption solves the keyword searching problem in a secure e-mail system, it also breaks the deniability of the system. Because the adversary can obtain the information of the data sender and data user from the trapdoor as well as ciphertext...

We introduce a new cryptographic primitive, called Sybil-Resilient Anonymous (SyRA) signatures, which enable users to generate, on demand, unlinkable pseudonyms tied to any given context, and issue signatures on behalf of these pseudonyms. Concretely, given a personhood relation, an issuer (who may be a distributed entity) enables users to prove their personhood and extract an associated long-term key, which can then be used to issue signatures for any given context and message....

In recent years, decentralized computing has gained popularity in various domains such as decentralized learning, financial services and the Industrial Internet of Things. As identity privacy becomes increasingly important in the era of big data, safeguarding user identity privacy while ensuring the security of decentralized computing systems has become a critical challenge. To address this issue, we propose ADC (Anonymous Decentralized Computing) to achieve anonymity in decentralized...

Insight into user experience and behavior is critical to the success of large software systems and web services. Gaining such insights, while preserving user privacy, is a significant challenge. Recent advancements in multi-party computation have made it practical to securely compute aggregates over secret shared data. Two such protocols have emerged as candidates for standardization at the IETF: Prio (NSDI 2017) for general-purpose statistics; and Poplar (IEEE S&P 2021) for heavy hitters,...

Recommender systems are effective mechanisms for recommendations about what to watch, read, or taste based on user ratings about experienced products or services. To achieve higher quality recommendations, e-commerce parties may prefer to collaborate over partitioned data. Due to privacy issues, they might hesitate to work in pairs and some solutions motivate them to collaborate. This study examines how to estimate trust-based predictions on arbitrarily partitioned data in which two...

We propose a solution for user privacy-oriented privacy-preserving data aggregation with multiple data customers. Most existing state-of-the-art approaches present too much importance on performance efficiency and seem to ignore privacy properties except for input privacy. Most solutions for data aggregation do not generally discuss the users’ birthright, namely their privacy for their own data control and anonymity when they search for something on the browser or volunteer to participate in...

IDentity-based Password Authentication and Key Establishment (ID-PAKE) is an interesting trade-off between the security and efficiency, specially due to the removal of costly Public Key Infrastructure (PKI). However, we observe that previous PAKE schemes such as Beguinet et al. (ACNS 2023), Pan et al. (ASIACRYPT 2023) , Abdallah et al. (CRYPTO 2020) etc. fail to achieve important security properties such as weak/strong Perfect Forward Secrecy (s-PFS), user authentication and resistance to...

We consider how to design an anonymous data collection protocol that enforces compliance rules. Imagine that each client contributes multiple data items (e.g., votes, location crumbs, or secret shares of its input) to an anonymous network, which mixes all clients' data items so that the receiver cannot determine which data items belong to the same user. Now, each user must prove to an auditor that the set it contributed satisfies a compliance predicate, without identifying which items it...

Anonymous credential schemes enable service providers to verify information that a credential holder willingly discloses, without needing any further personal data to corroborate that information, and without allowing the user to be tracked from one interaction to the next. Mercurial signatures are a novel class of anonymous credentials which show good promise as a simple and efficient construction without heavy reliance on zero-knowledge proofs. However, they still require significant...

Decentralized Finance (DeFi) has witnessed remarkable growth and innovation, with Decentralized Exchanges (DEXes) playing a pivotal role in shaping this ecosystem. As numerous DEX designs emerge, challenges such as price inefficiency and lack of user privacy continue to prevail. This paper introduces a novel DEX design, termed COMMON, that addresses these two predominant challenges. COMMON operates as an order book, natively integrated with a shielded token pool, thus providing anonymity to...

While blockchain technologies leverage compelling characteristics in terms of decentralization, immutability, and transparency, user privacy in public blockchains remains a fundamental challenge that requires particular attention. This is mainly due to the history of all transactions being accessible and available to anyone, thus making it possible for an attacker to infer data about users that is supposed to remain private. In this paper, we provide a threat model of possible privacy...

Decentralized payment systems have gradually received more attention in recent years. By removing the trusted intermediary used for accounting ledgers, those payment systems fundamentally empower users to control their assets. As privacy concerns grow, some cryptocurrencies are proposed to preserve the privacy of users. However, those cryptocurrencies also inadvertently facilitate illicit activities such as money laundering, fraudulent trading, etc. So it is necessary to design an auditing...

The privacy pass protocol allows users to redeem anonymously issued cryptographic tokens instead of solving annoying CAPTCHAs. The issuing authority verifies the credibility of the user, who can later use the pass while browsing the web using an anonymous or virtual private network. Hendrickson et al. proposed an IETF draft (privacypass-rate-limit-tokens-00) for a rate-limiting version of the privacy pass protocol, also called rate-limited Privacy Pass (RlP). Introducing a new actor called a...

Privacy enhancing technologies must not only protect sensitive data in-transit, but also locally at-rest. For example, anonymity networks hide the sender and/or recipient of a message from network adversaries. However, if a participating device is physically captured, its owner can be pressured to give access to the stored conversations. Therefore, client software should allow the user to plausibly deny the existence of meaningful data. Since biometrics can be collected without consent and...

Privacy-preserving blueprint schemes (Kohlweiss et al., EUROCRYPT'23) offer a mechanism for safeguarding user's privacy while allowing for specific legitimate controls by a designated auditor agent. These schemes enable users to create escrows encrypting the result of evaluating a function $y=P(t,x)$, with $P$ being publicly known, $t$ a secret used during the auditor's key generation, and $x$ the user's private input. Crucially, escrows only disclose the blueprinting result $y=P(t,x)$...

As various industries and government agencies increasingly seek to build quantum computers, the development of post-quantum constructions for different primitives becomes crucial. Lattice-based cryptography is one of the top candidates for constructing quantum-resistant primitives. In this paper, we propose a decentralized Private Stream Aggregation (PSA) protocol based on the Learning with Errors (LWE) problem. PSA allows secure aggregation of time-series data over multiple users without...

How to achieve distributed differential privacy (DP) without a trusted central party is of great interest in both theory and practice. Recently, the shuffle model has attracted much attention. Unlike the local DP model in which the users send randomized data directly to the data collector/analyzer, in the shuffle model an intermediate untrusted shuffler is introduced to randomly permute the data, which have already been randomized by the users, before they reach the analyzer. The most...

Security of model parameters and user data is critical for Transformer-based services, such as ChatGPT. While recent strides in secure two-party protocols have successfully addressed security concerns in serving Transformer models, their adoption is practically infeasible due to the prohibitive cryptographic overheads involved. Drawing insights from our hands-on experience in developing two real-world Transformer-based services, we identify the inherent efficiency bottleneck in the...

Security proofs of symmetric-key primitives typically consider an idealized world with access to a (uniformly) random function. The starting point of our work is the observation that such an ideal world can lead to underestimating the actual security of certain primitives. As a demonstrating example, $\mathsf{XoP2}$, which relies on two independent random permutations, has been proven to exhibit superior concrete security compared to $\mathsf{XoP}$, which employs a single permutation with...

Classic MLaaS solutions suffer from privacy-related risks since the user is required to send unencrypted data to the server hosting the MLaaS. To alleviate this problem, a thriving line of research has emerged called Privacy-Preserving Machine Learning (PPML) or secure MLaaS solutions that use cryptographic techniques to preserve the privacy of both the input of the client and the output of the server. However, these implementations do not take into consideration the possibility of...

The global lockdown imposed during the Covid-19 pandemic has resulted in significant social and economic challenges. In an effort to reopen economies and simultaneously control the spread of the disease, the implementation of contact tracing and digital vaccine passport technologies has been introduced. While contact tracing methods have been extensively studied and scrutinized for security concerns through numerous publications, vaccine passports have not received the same level of...

Private Information Retrieval (PIR) is a cryptographic primitive that allows a user to access data from a database without disclosing the specific information being requested, thereby safeguarding privacy. PIR schemes suffer from a significant computational burden. By running an offline preprocessing phase, PIR schemes can achieve sublinear online computation. While protocols for semi-honest servers have been well-studied in both single-server and multi-server scenarios, scant attention has...

Key Transparency (KT) refers to a public key distribution system with transparency mechanisms proving its correct operation, i.e., proving that it reports consistent values for each user's public key. While prior work on KT systems have offered new designs to tackle this problem, relatively little attention has been paid on the issue of scalability. Indeed, it is not straightforward to actually build a scalable and practical KT system from existing constructions, which may be too complex,...

Central banks around the world are actively exploring the issuance of retail central bank digital currency (rCBDC), which is widely seen as a key upgrade of the monetary system in the 21st century. However, privacy concerns are the main impediment to rCBDC’s development and roll-out. A central bank as the issuer of rCBDC would typically need to keep a digital ledger to record all the balances and transactions of citizens. These data, when combined with other data, could possibly disclose the...

The well-defined information leakage of Encrypted Search Algorithms (ESAs) is predominantly analyzed by crafting so-called leakage attacks. These attacks utilize adversarially known auxiliary data and the observed leakage to attack an ESA instance built on a user's data. Known-data attacks require the auxiliary data to be a subset of the user's data. In contrast, sampled-data attacks merely rely on auxiliary data that is, in some sense, statistically close to the user's data and hence...

FIDO2 is currently the main initiative for passwordless authentication in web servers. It mandates the use of secure hardware authenticators to protect the authentication protocol’s secrets from compromise. However, to ensure that only secure authenticators are being used, web servers need a method to attest their properties. The FIDO2 specifications allow for authenticators and web servers to choose between different attestation modes to prove the characteristics of an authenticator,...

Over the last decade, online reputation has become a central aspect of our digital lives. Most online services and communities assign a reputation score to users, based on feedback from other users about various criteria such as how reliable, helpful, or knowledgeable a person is. While many online services compute reputation based on the same set of such criteria, users currently do not have the ability to use their reputation scores across services. As a result, users face trouble...

User privacy is becoming increasingly important in our digital society. Yet, many applications face legal requirements or regulations that prohibit unconditional anonymity guarantees, e.g., in electronic payments where surveillance is mandated to investigate suspected crimes. As a result, many systems have no effective privacy protections at all, or have backdoors, e.g., stored at the operator side of the system, that can be used by authorities to disclose a user’s private information...

Location tracking accessories (or "tracking tags") such as those sold by Apple, Samsung, and Tile, allow owners to track the location of their property via offline finding networks. The tracking protocols were designed to ensure that no entity (including the vendor) can use a tag's broadcasts to surveil its owner. These privacy guarantees, however, seem to be at odds with the phenomenon of $\textit{tracker-based stalking}$, where attackers use these very tags to monitor a target's...

Cryptocurrency exchange platforms such as Coinbase, Binance, enable users to purchase and sell cryptocurrencies conveniently just like trading stocks/commodities. However, because of the nature of blockchain, when a user withdraws coins (i.e., transfers coins to an external on-chain account), all future transactions can be learned by the platform. This is in sharp contrast to conventional stock exchange where all external activities of users are always hidden from the platform. Since the...

This work formally analyzes the anonymity guarantees of continuous stop-and-go mixnets and attempts to answer the above question. Existing mixnet based anonymous communication protocols that aim to provide provable anonymity guarantees rely on round-based communication models --- which requires synchronization among all the nodes and clients, and difficult to achieve in practice. Continuous stop-and-go mixnets (e.g., Loopix and Nym) provide a nice alternative by adding a random delay for...

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...

Recently, the FinTracer algorithm was introduced as a versatile framework for detecting economic crime typologies in a privacy-preserving fashion. Under the hood, FinTracer stores its data in a structure known as the ``FinTracer tag’’. One limitation of FinTracer tags, however, is that because their underlying cryptographic implementation relies on additive semi-homomorphic encryption, all the system's oblivious computations on tag data are linear in their input ciphertexts. This allows a...

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...

Contact discovery is a crucial component of social applications, facilitating interactions between registered contacts. This work introduces Arke, a novel approach to contact discovery that addresses the limitations of existing solutions in terms of privacy, scalability, and reliance on trusted third parties. Arke ensures the unlinkability of user interactions, mitigates enumeration attacks, and operates without single points of failure or trust. Notably, Arke is the first contact discovery...

Anonymous tokens are digital signature schemes that enable an issuer to provider users with signatures without learning the input message or the resulting signature received by the user. These primitives allow applications to propagate trust while simultaneously protecting the identity of the user. Anonymous tokens have become a core component for improving the privacy of several real-world applications including ad measurements, authorization protocols, spam detection and VPNs. In...

The accelerated advances in information communication technologies have made it possible for enterprises to deploy large scale applications in a multi-server architecture (also known as cloud computing environment). In this architecture, a mobile user can remotely obtain desired services over the Internet from multiple servers by initially executing a single registration on a trusted registration server (RS). Due to the hazardous nature of the Internet, to protect user privacy and online...

Vehicle-to-grid (V2G) networks, as an emerging smart grid paradigm, can be integrated with renewable energy resources to provide power services and manage electricity demands. When accessing electricity services, an electric vehicle(EV) typically provides authentication or/and payment information containing identifying data to a service provider, which raises privacy concerns as malicious entities might trace EV activity or exploit personal information. Although numerous anonymous...

A linkable ring signature allows a user to sign anonymously on behalf of a group while ensuring that multiple signatures from the same user are detected. Applications such as privacy-preserving e-voting and e-cash can leverage linkable ring signatures to significantly improve privacy and anonymity guarantees. To scale to systems involving large numbers of users, short signatures with fast verification are a must. Concretely efficient ring signatures currently rely on a trusted authority...

Blockchains enable mutually distrustful parties to perform financial operations in a trustless, decentralized, publicly-verifiable environment. Blockchains typically offer little privacy, and thus motivated the construction of privacy mixers, a solution to make funds untraceable. Privacy mixers concern regulators due to their increasing use by bad actors to illegally conceal the origin of funds. Consequently, Tornado Cash, the largest privacy mixer to date, is sanctioned by large portions of...

ChatGPT is recognized as a significant revolution in the field of artificial intelligence, but it raises serious concerns regarding user privacy, as the data submitted by users may contain sensitive information. Existing solutions for secure inference face significant challenges in supporting GPT-like models due to the enormous number of model parameters and complex activation functions. In this paper, we develop CipherGPT, the first framework for secure two-party GPT inference, building...

Commodity encrypted storage platforms (e.g., IceDrive, pCloud) permit data store and sharing across multiple users while preserving data confidentiality. However, end-to-end encryption may not be sufficient since it only offers confidentiality when the data is at rest or in transit. Meanwhile, sensitive information can be leaked from metadata representing activities during data operations (e.g., query, processing). Recent encrypted search platforms such as DORY (OSDI’20) or DURASIFT...

Privacy-preserving payment systems face the difficult task of balancing privacy and accountability: on one hand, users should be able to transact privately and anonymously, on the other hand, no illegal activities should be tolerated. The challenging question of finding the right balance lies at the core of the research on accountable privacy that stipulates the use of cryptographic techniques for policy enforcement. Current state-of-the-art systems are only able to enforce rather limited...

During the pandemic, the limited functionality of existing privacy-preserving contact tracing systems highlights the need for new designs. Wang et al. proposed an environmental-adaptive framework (CSS '21) but failed to formalize the security. The similarity between their framework and attribute-based credentials (ABC) inspires us to reconsider contact tracing from the perspective of ABC schemes. In such schemes, users can obtain credentials on attributes from issuers and prove the...

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...

Anonymous credentials (AC) have emerged as a promising privacy-preserving solu- tion for user-centric identity management. They allow users to authenticate in an anonymous and unlinkable way such that only required information (i.e., attributes) from their credentials are re- vealed. With the increasing push towards decentralized systems and identity, e.g., self-sovereign identity (SSI) and the concept of verifiable credentials, this also necessitates the need for suit- able AC systems. For...

In this paper, we present a novel method for timestamping and data notarisation on a distributed ledger. The problem with on-chain hashes is that a cryptographic hash is a deterministic function that it allows the blockchain be used as an oracle that confirms whether potentially leaked data is authentic (timestamped or notarised by the user). Instead, we suggest using on-chain Pedersen commitments and off-chain zero knowledge proofs (ZKP) for designated verifiers to prove the link between...

Society appears to be on the verge of recognizing the need for control over sensitive data in modern web applications. Recently, many systems claim to give control to individuals, promising the preeminent goal of data sovereignty. However, despite recent attention, research and industry efforts are fragmented and lack a holistic system overview. In this paper, we provide the first transecting systematization of data sovereignty by drawing from a dispersed body of knowledge. We clarify the...