Aggregate Pseudorandom Functions and Connections to Learning

In the first part of this work, we introduce a new type of pseudo-random function for which ``aggregate queries\u27\u27 over exponential-sized sets can be efficiently answered. We show how to use algebraic properties of underlying classical pseudo random functions, to construct such ``aggregate pseudo-random functions\u27\u27 for a number of classes of aggregation queries under cryptographic hardness assumptions. For example, one aggregate query we achieve is the product of all function values accepted by a polynomial-sized read-once boolean formula. On the flip side, we show that certain aggregate queries are impossible to support. Aggregate pseudo-random functions fall within the framework of the work of Goldreich, Goldwasser, and Nussboim on the ``Implementation of Huge Random Objects,\u27\u27 providing truthful implementations of pseudo-random functions for which aggregate queries can be answered. In the second part of this work, we show how various extensions of pseudo-random functions considered recently in the cryptographic literature, yield impossibility results for various extensions of machine learning models, continuing a line of investigation originated by Valiant and Kearns in the 1980s. The extended pseudo-random functions we address include constrained pseudo random functions, aggregatable pseudo random functions, and pseudo random functions secure under related-key attacks

XYZ Privacy

Future autonomous vehicles will generate, collect, aggregate and consume significant volumes of data as key gateway devices in emerging Internet of Things scenarios. While vehicles are widely accepted as one of the most challenging mobility contexts in which to achieve effective data communications, less attention has been paid to the privacy of data emerging from these vehicles. The quality and usability of such privatized data will lie at the heart of future safe and efficient transportation solutions. In this paper, we present the XYZ Privacy mechanism. XYZ Privacy is to our knowledge the first such mechanism that enables data creators to submit multiple contradictory responses to a query, whilst preserving utility measured as the absolute error from the actual original data. The functionalities are achieved in both a scalable and secure fashion. For instance, individual location data can be obfuscated while preserving utility, thereby enabling the scheme to transparently integrate with existing systems (e.g. Waze). A new cryptographic primitive Function Secret Sharing is used to achieve non-attributable writes and we show an order of magnitude improvement from the default implementation.Comment: arXiv admin note: text overlap with arXiv:1708.0188

Prio+: Privacy Preserving Aggregate Statistics via Boolean Shares

This paper introduces Prio+, a privacy-preserving system for the collection of aggregate statistics, with the same model and goals in mind as the original and highly influential Prio paper by Henry Corrigan-Gibbs and Dan Boneh (USENIX 2017). As in the original Prio, each client holds a private data value (e.g. number of visits to a particular website) and a small set of servers privately compute statistical functions over the set of client values (e.g. the average number of visits). To achieve security against faulty or malicious clients, Prio+ clients use Boolean secret-sharing instead of zero-knowledge proofs to convince servers that their data is of the correct form and Prio+ servers execute a share conversion protocols as needed in order to properly compute over client data. This allows us to ensure that clients’ data is properly formatted essentially for free, and the work shifts to novel share-conversion protocols between servers, where some care is needed to make it efficient. While our overall approach is a fairly simple observation in retrospect, it turns out that Prio+ strategy reduces the client’s computational burden by up to two orders of magnitude (or more depending on the statistic) while keeping servers costs comparable to Prio. Prio+ permits computation of exactly the same wide range of complex statistics as the original Prio protocol, including high-dimensional linear regression over private values held by clients. We report detailed benchmarks of our Prio+ implementation and compare these to both the original Go implementation of Prio and the Mozilla implementation of Prio. Our Prio+ software is open-source and released with the same license as Prio

End-to-End Encrypted Group Messaging with Insider Security

Our society has become heavily dependent on electronic communication, and preserving the integrity of this communication has never been more important. Cryptography is a tool that can help to protect the security and privacy of these communications. Secure messaging protocols like OTR and Signal typically employ end-to-end encryption technology to mitigate some of the most egregious adversarial attacks, such as mass surveillance. However, the secure messaging protocols deployed today suffer from two major omissions: they do not natively support group conversations with three or more participants, and they do not fully defend against participants that behave maliciously. Secure messaging tools typically implement group conversations by establishing pairwise instances of a two-party secure messaging protocol, which limits their scalability and makes them vulnerable to insider attacks by malicious members of the group. Insiders can often perform attacks such as rendering the group permanently unusable, causing the state of the group to diverge for the other participants, or covertly remaining in the group after appearing to leave. It is increasingly important to prevent these insider attacks as group conversations become larger, because there are more potentially malicious participants. This dissertation introduces several new protocols that can be used to build modern communication tools with strong security and privacy properties, including resistance to insider attacks. Firstly, the dissertation addresses a weakness in current two-party secure messaging tools: malicious participants can leak portions of a conversation alongside cryptographic proof of authorship, undermining confidentiality. The dissertation introduces two new authenticated key exchange protocols, DAKEZ and XZDH, with deniability properties that can prevent this type of attack when integrated into a secure messaging protocol. DAKEZ provides strong deniability in interactive settings such as instant messaging, while XZDH provides deniability for non-interactive settings such as mobile messaging. These protocols are accompanied by composable security proofs. Secondly, the dissertation introduces Safehouse, a new protocol that can be used to implement secure group messaging tools for a wide range of applications. Safehouse solves the difficult cryptographic problems at the core of secure group messaging protocol design: it securely establishes and manages a shared encryption key for the group and ephemeral signing keys for the participants. These keys can be used to build chat rooms, team communication servers, video conferencing tools, and more. Safehouse enables a server to detect and reject protocol deviations, while still providing end-to-end encryption. This allows an honest server to completely prevent insider attacks launched by malicious participants. A malicious server can still perform a denial-of-service attack that renders the group unavailable or "forks" the group into subgroups that can never communicate again, but other attacks are prevented, even if the server colludes with a malicious participant. In particular, an adversary controlling the server and one or more participants cannot cause honest participants' group states to diverge (even in subtle ways) without also permanently preventing them from communicating, nor can the adversary arrange to covertly remain in the group after all of the malicious participants under its control are removed from the group. Safehouse supports non-interactive communication, dynamic group membership, mass membership changes, an invitation system, and secure property storage, while offering a variety of configurable security properties including forward secrecy, post-compromise security, long-term identity authentication, strong deniability, and anonymity preservation. The dissertation includes a complete proof-of-concept implementation of Safehouse and a sample application with a graphical client. Two sub-protocols of independent interest are also introduced: a new cryptographic primitive that can encrypt multiple private keys to several sets of recipients in a publicly verifiable and repeatable manner, and a round-efficient interactive group key exchange protocol that can instantiate multiple shared key pairs with a configurable knowledge relationship

Actas de las VI Jornadas Nacionales (JNIC2021 LIVE)

Estas jornadas se han convertido en un foro de encuentro de los actores más relevantes en el ámbito de la ciberseguridad en España. En ellas, no sólo se presentan algunos de los trabajos científicos punteros en las diversas áreas de ciberseguridad, sino que se presta especial atención a la formación e innovación educativa en materia de ciberseguridad, y también a la conexión con la industria, a través de propuestas de transferencia de tecnología. Tanto es así que, este año se presentan en el Programa de Transferencia algunas modificaciones sobre su funcionamiento y desarrollo que han sido diseñadas con la intención de mejorarlo y hacerlo más valioso para toda la comunidad investigadora en ciberseguridad

Pseudorandom functions with structure : aggregate pseudorandom functions and connections to learning

Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2015.Title as it appears in MIT Commencement Exercises program, June 5, 2015: Pseudorandom functions with structure : aggregate pseudorandom functions and connections to learning Cataloged from PDF version of thesis.Includes bibliographical references (pages 79-82).In the first part of this work, we introduce a new type of pseudo-random function for which "aggregate queries" over exponential-sized sets can be efficiently answered. We show how to use algebraic properties of underlying classical pseudo random functions, to construct such "aggregate pseudo-random functions" for a number of classes of aggregation queries under cryptographic hardness assumptions. For example, one aggregate query we achieve is the product of all function values accepted by a polynomial-sized read-once boolean formula. On the flip side, we show that certain aggregate queries are impossible to support. In the second part of this work, we show how various extensions of pseudo-random functions considered recently in the cryptographic literature, yield impossibility results for various extensions of machine learning models, continuing a line of investigation originated by Valiant and Kearns in the 1980s. The extended pseudo-random functions we address include constrained pseudo random functions, aggregatable pseudo random functions, and pseudo random functions secure under related-key attacks. In the third part of this work, we demonstrate limitations of the recent notions of constrained pseudo-random functions and cryptographic watermarking schemes. Specifically, we construct pseudorandom function families that can be neither punctured nor watermarked. This is achieved by constructing new unobfuscatable pseudorandom function families for new ranges of parameters.by Aloni Cohen.S.M