International Association for Cryptologic Research

International Association
for Cryptologic Research

CryptoDB

Duong Hieu Phan

Publications

Year
Venue
Title
2020
PKC
Linearly-Homomorphic Signatures and Scalable Mix-Nets 📺
Anonymity is a primary ingredient for our digital life. Several tools have been designed to address it such as, for authentication, blind signatures, group signatures or anonymous credentials and, for confidentiality, randomizable encryption or mix-nets. When it comes to complex electronic voting schemes, random shuffling of authenticated ciphertexts with mix-nets is the only known tool. However, it requires huge and complex zero-knowledge proofs to guarantee the actual permutation of the initial ciphertexts in a privacy-preserving way. In this paper, we propose a new approach for proving correct shuffling of signed ElGamal ciphertexts: the mix-servers can simply randomize individual ballots, which means the ciphertexts, the signatures, and the verification keys, with an additional global proof of constant size, and the output will be publicly verifiable. The security proof is in the generic bilinear group model. The computational complexity for the each mix-server is linear in the number of ballots. Verification is also linear in the number of ballots, but independent of the number of rounds of mixing. This leads to a new highly scalable technique. Our construction makes use of linearly-homomorphic signatures, with new features, that are of independent interest.
2020
CRYPTO
Dynamic Decentralized Functional Encryption 📺
We introduce Dynamic Decentralized Functional Encryption (DDFE), a generalization of Functional Encryption which allows multiple users to join the system dynamically, without relying on a trusted third party or on expensive and interactive Multi-Party Computation protocols. This notion subsumes existing multi-user extensions of Functional Encryption, such as Multi-Input, Multi-Client, and Ad Hoc Multi-Input Functional Encryption. We define and construct schemes for various functionalities which serve as building-blocks for latter primitives and may be useful in their own right, such as a scheme for dynamically computing sums in any Abelian group. These constructions build upon simple primitives in a modular way, and have instantiations from well-studied assumptions, such as DDH or LWE. Our constructions culminate in an Inner-Product scheme for computing weighted sums on aggregated encrypted data, from standard assumptions in prime-order groups in the Random Oracle Model.
2020
ASIACRYPT
Catalic: Delegated PSI Cardinality with Applications to Contact Tracing 📺
Thai Duong Duong Hieu Phan Ni Trieu
Private Set Intersection Cardinality (PSI-CA) allows two parties, each holding a set of items, to learn the size of the intersection of those sets without revealing any additional information. To the best of our knowledge, this work presents the first protocol that allows one of the parties to delegate PSI-CA computation to untrusted servers. At the heart of our delegated PSI-CA protocol is a new oblivious distributed key PRF (Odk-PRF) abstraction, which may be of independent interest. We explore in detail how to use our delegated PSI-CA protocol to perform privacy-preserving contact tracing. It has been estimated that a significant percentage of a given population would need to use a contact tracing app to stop a disease’s spread. Prior privacy-preserving contact tracing systems, however, impose heavy bandwidth or computational demands on client devices. These demands present an economic disincentive to participate for end users who may be billed per MB by their mobile data plan or for users who want to save battery life. We propose Catalic (ContAct TrAcing for LIghtweight Clients), a new contact tracing system that minimizes bandwidth cost and computation workload on client devices. By applying our new delegated PSI-CA protocol, Catalic shifts most of the client-side computation of contact tracing to untrusted servers, and potentially saves each user hundreds of megabytes of mobile data per day while preserving privacy.
2018
ASIACRYPT
Decentralized Multi-Client Functional Encryption for Inner Product
We consider a situation where multiple parties, owning data that have to be frequently updated, agree to share weighted sums of these data with some aggregator, but where they do not wish to reveal their individual data, and do not trust each other. We combine techniques from Private Stream Aggregation (PSA) and Functional Encryption (FE), to introduce a primitive we call Decentralized Multi-Client Functional Encryption (DMCFE), for which we give a practical instantiation for Inner Product functionalities. This primitive allows various senders to non-interactively generate ciphertexts which support inner-product evaluation, with functional decryption keys that can also be generated non-interactively, in a distributed way, among the senders. Interactions are required during the setup phase only. We prove adaptive security of our constructions, while allowing corruptions of the clients, in the random oracle model.
2017
CRYPTO
2014
CRYPTO
2014
EPRINT
2009
EUROCRYPT
2007
PKC
2005
EUROCRYPT
2004
ASIACRYPT
2003
ASIACRYPT

Program Committees

Asiacrypt 2020
Asiacrypt 2019
Asiacrypt 2014
PKC 2010
Eurocrypt 2009