Probabilistic data structures (PDS) are compact representations of high-volume data that provide approximate answers to queries about the data. They are commonplace in today's computing systems, finding use in databases, networking and more. While PDS are designed to perform well under benign inputs, they are frequently used in applications where inputs may be adversarially chosen. This may lead to a violation of their expected behaviour, for example an increase in false positive rate. In...

Private set intersections are cryptographic protocols that compute the intersection of multiple parties' private sets without revealing elements that are not in the intersection. These protocols become less efficient when the number of parties grows, or the size of the sets increases. For this reason, many protocols are based on Bloom filters, which speed up the protocol by approximating the intersections, introducing false positives with a small but non-negligible probability. These false...

Redis (Remote Dictionary Server) is a general purpose, in-memory database that supports a rich array of functionality, including various Probabilistic Data Structures (PDS), such as Bloom filters, Cuckoo filters, as well as cardinality and frequency estimators. These PDS typically perform well in the average case. However, given that Redis is intended to be used across a diverse array of applications, it is crucial to evaluate how these PDS perform under worst-case scenarios, i.e., when...

Privacy Set Intersection (PSI) has been an important research topic within privacy computation. Its main function is to allow two parties to compute the intersection of their private sets without revealing any other private information. Therefore, PSI can be applied to various real-world scenarios. Chase and Miao presented an impressive construction ``Private set intersection in the Internet setting from lightweight oblivious prf'' (CM20 for short) at Crypto 2020, highlighting its...

The Learned Bloom Filter is a recently proposed data structure that combines the Bloom Filter with a Learning Model while preserving the Bloom Filter's one-sided error guarantees. Creating an adversary-resilient construction of the Learned Bloom Filter with provable guarantees is an open problem. We define a strong adversarial model for the Learned Bloom Filter. Our adversarial model extends an existing adversarial model designed for the Classical (i.e. not ``Learned'') Bloom Filter by prior...

We describe a small tweak to Cuckoo filters that allows securing them under insertions using the techniques from Filić et al. (ACM CCS 2022), without the need for an outer PRF call.

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...

Count-Min Sketch (CMS) and HeavyKeeper (HK) are two realizations of a compact frequency estimator (CFE). These are a class of probabilistic data structures that maintain a compact summary of (typically) high-volume streaming data, and provides approximately correct estimates of the number of times any particular element has appeared. CFEs are often the base structure in systems looking for the highest-frequency elements (i.e., top-$K$ elements, heavy hitters, elephant flows). ...

In data-intensive private computing applications various relations appear as or can be reduced to matrix relations. In this paper we investigate two problems related to constructing the zero-knowledge argument (ZKA) protocols for matrix relations (in commit-and-prove paradigm). In the first part, we establish the ZKA for some bilinear matrix relations over Fp. The relations in consideration include (1) general forms of bilinear relations with two witness matrices and some most important...

Quantum computing advances threaten the security of today's public key infrastructure, and have led to the pending standardization of alternative, quantum-resistant key encapsulation and digital signature cryptography schemes. Unfortunately, authentication algorithms based on the new post-quantum (PQ) cryptography create significant performance bottlenecks for TLS due to larger certificate chains which introduce additional packets and round-trips. The TLS handshake slowdown will be...

A Bloom filter is a data structure that maintains a succinct and probabilistic representation of a set $S\subseteq U$ of elements from a universe $U$. It supports approximate membership queries. The price of the succinctness is allowing some error, namely false positives: for any $x\notin S$, it might answer `Yes' but with a small (non-negligible) probability. When dealing with such data structures in adversarial settings, we need to define the correctness guarantee and formalize the...

We study the security of Probabilistic Data Structures (PDS) for handling Approximate Membership Queries (AMQ); prominent examples of AMQ-PDS are Bloom and Cuckoo filters. AMQ-PDS are increasingly being deployed in environments where adversaries can gain benefit from carefully selecting inputs, for example to increase the false positive rate of an AMQ-PDS. They are also being used in settings where the inputs are sensitive and should remain private in the face of adversaries who can...

Recent years have seen a strong uptick in both the prevalence and real-world consequences of false information spread through online platforms. At the same time, encrypted messaging systems such as WhatsApp, Signal, and Telegram, are rapidly gaining popularity as users seek increased privacy in their digital lives. The challenge we address is how to combat the viral spread of misinformation without compromising privacy. Our FACTS system tracks user complaints on messages obliviously, only...

Probabilistic data structures use space-efficient representations of data in order to (approximately) respond to queries about the data. Traditionally, these structures are accompanied by probabilistic bounds on query-response errors. These bounds implicitly assume benign attack models, in which the data and the queries are chosen non-adaptively, and independent of the randomness used to construct the representation. Yet probabilistic data structures are increasingly used in settings where...

End-to-end encrypted databases have been heavily studied in the last two decades. A crucial aspect that previous work has neglected, however, is that real-world databases are distributed in the sense that data is partitioned among a cluster of nodes---as opposed to being stored on a single node. In this work, we initiate the study of encrypted distributed data structures which are end-to-end encrypted variants of distributed data structures; themselves fundamental to the design of...

We introduce and study the notion of fully linear probabilistically checkable proof systems. In such a proof system, the verifier can make a small number of linear queries that apply jointly to the input and a proof vector. Our new type of proof system is motivated by applications in which the input statement is not fully available to any single verifier, but can still be efficiently accessed via linear queries. This situation arises in scenarios where the input is partitioned or...

The recently proposed Oblivious Cross-Tags (OXT) protocol (CRYPTO 2013) has broken new ground in designing efficient searchable symmetric encryption (SSE) protocol with support for conjunctive keyword search in a single-writer single-reader framework. While the OXT protocol offers high performance by adopting a number of specialised data-structures, it also trades-off security by leaking ‘partial’ database information to the server. Recent attacks have exploited similar partial information...

Structured encryption (STE) schemes encrypt data structures in such a way that they can be privately queried. One aspect of STE that is still poorly understood is its leakage. In this work, we describe a general framework to design STE schemes that do not leak the query/search pattern (i.e., if and when a query was previously made). Our framework consists of two compilers. The first can be used to make any dynamic STE scheme rebuildable in the sense that the encrypted structures it...

Forward secrecy is considered an essential design goal of modern key establishment (KE) protocols, such as TLS 1.3, for example. Furthermore, efficiency considerations such as zero round-trip time (0-RTT), where a client is able to send cryptographically protected payload data along with the very first KE message, are motivated by the practical demand for secure low-latency communication. For a long time, it was unclear whether protocols that simultaneously achieve 0-RTT and full forward...

Many efficient data structures use randomness, allowing them to improve upon deterministic ones. Usually, their efficiency and correctness are analyzed using probabilistic tools under the assumption that the inputs and queries are independent of the internal randomness of the data structure. In this work, we consider data structures in a more robust model, which we call the adversarial model. Roughly speaking, this model allows an adversary to choose inputs and queries adaptively according...

Although newly proposed, tree-based Oblivious RAM schemes are drastically more efficient than older techniques, they come with a significant drawback: an inherent dependence on a fixed-size database. This capability is vital for real-world use of Oblivious RAM since one of its most promising deployment scenarios is for cloud storage, where scalability and elasticity are crucial. We revisit the original construction by Shi et al. [16] and propose several ways to support both increasing and...

Privacy is faced to serious challenges in the ubiquitous computing world. In order to handle this problem, some researches in recent years have focused on design and analysis of privacy friendly ultralightweight authentication protocols. In less than a decade, many ultralightweight authentication protocols are proposed. Though, successful crypanalyses are proposed for almost all of them, most of these attacks are based on ad-hoc methods that are not extensible to a large class of...

We propose QTRU, a probabilistic and multi-dimensional public key cryptosystem based on the NTRU public key cryptosystem using quaternion algebra. QTRU encrypts four data vectors in each encryption session and the only other major di®erence between NTRU and QTRU is that the underlying algebraic structure has been changed to a non-commutative algebraic structure. As a result, QTRU inherits the strength of NTRU and its positive points. In addition, the non commutativity of the underlying...

We propose QTRU, a probabilistic and multi-dimensional public key cryptosystem based on the NTRU public key cryptosystem using quaternion algebra. QTRU encrypts four data vectors in each encryption session and the only other major difference between NTRU and QTRU is that the underlying algebraic structure has been changed to a non-commutative algebraic structure. As a result, QTRU inherits the strength of NTRU and its positive points. In addition, the non-commutativity of the underlying...