International Association for Cryptologic Research

International Association
for Cryptologic Research

CryptoDB

Rachit Garg

Publications

Year
Venue
Title
2022
EUROCRYPT
Dynamic Collusion Bounded Functional Encryption from Identity-Based Encryption
Functional Encryption is a powerful notion of encryption in which each decryption key is associated with a function f such that decryption recovers the function evaluation f(m). Informally, security states that a user with access to function keys sk_f1,sk_f2,..., (and so on) can only learn f1(m), f2(m),... (and so on) but nothing more about the message. The system is said to be q-bounded collusion resistant if the security holds as long as an adversary gets access to at most q = q(λ) function keys. A major drawback of such statically bounded collusion systems is that the collusion bound q must be declared at setup time and is fixed for the entire lifetime of the system. We initiate the study of dynamically bounded collusion resistant functional encryption systems which provide more flexibility in terms of selecting the collusion bound, while reaping the benefits of statically bounded collusion FE systems (such as quantum resistance, simulation security, and general assumptions). Briefly, the virtues of a dynamically bounded scheme can be summarized as: -Fine-grained individualized selection: It lets each encryptor select the collusion bound by weighing the trade-off between performance overhead and the amount of collusion resilience. -Evolving encryption strategies: Since the system is no longer tied to a single collusion bound, thus it allows to dynamically adjust the desired collusion resilience based on any number of evolving factors such as the age of the system, or a number of active users, etc. -Ease and simplicity of updatability: None of the system parameters have to be updated when adjusting the collusion bound. That is, the same key skf can be used to decrypt ciphertexts for collusion bound q = 2 as well as q = 2^λ. We construct such a dynamically bounded functional encryption scheme for the class of all polynomial-size circuits under the general assumption of Identity-Based Encryption
2021
EUROCRYPT
Black-Box Non-Interactive Non-Malleable Commitments 📺
There has been recent exciting progress in building non-interactive non-malleable commitments from judicious assumptions. All proposed approaches proceed in two steps. First, obtain simple “base” commitment schemes for very small tag/identity spaces based on a various sub-exponential hardness assumptions. Next, assuming sub-exponential non-interactive witness indistinguishable proofs (NIWIs), and variants of keyless collision-resistant hash functions, construct non-interactive compilers that convert tag-based non-malleable commitments for a small tag space into tag-based non-malleable commitments for a larger tag space. We propose the first black-box construction of non-interactive non-malleable commitments. Our key technical contribution is a novel implementation of the non-interactive proof of consistency required for tag amplification. Prior to our work, the only known approach to tag amplification without setup and with black-box use of the base scheme (Goyal, Lee, Ostrovsky, and Visconti, FOCS 2012) added multiple rounds of interaction. Our construction satisfies the strongest known definition of non-malleability, i.e., CCA (chosen commitment attack) security. In addition to being black-box, our approach dispenses with the need for sub-exponential NIWIs, that was common to all prior work. Instead of NIWIs, we rely on sub-exponential hinting PRGs which can be obtained based on a broad set of assumptions such as sub-exponential CDH or LWE.
2020
TCC
New Techniques in Replica Encodings with Client Setup 📺
Rachit Garg George Lu Brent Waters
A proof of replication system is a cryptographic primitive that allows a server (or group of servers) to prove to a client that it is dedicated to storing multiple copies or replicas of a file. Until recently, all such protocols required fined-grained timing assumptions on the amount of time it takes for a server to produce such replicas. Damgard, Ganesh, and Orlandi [DGO19] proposed a novel notion that we will call proof of replication with client setup. Here, a client first operates with secret coins to generate the replicas for a file. Such systems do not inherently have to require fine-grained timing assumptions. At the core of their solution to building proofs of replication with client setup is an abstraction called replica encodings. Briefly, these comprise a private coin scheme where a client algorithm given a file m can produce an encoding \sigma. The encodings have the property that, given any encoding \sigma, one can decode and retrieve the original file m. Secondly, if a server has significantly less than n·|m| bit of storage, it cannot reproduce n encodings. The authors give a construction of encodings from ideal permutations and trapdoor functions. In this work, we make three central contributions: 1) Our first contribution is that we discover and demonstrate that the security argument put forth by [DGO19] is fundamentally flawed. Briefly, the security argument makes assumptions on the attacker's storage behavior that does not capture general attacker strategies. We demonstrate this issue by constructing a trapdoor permutation which is secure assuming indistinguishability obfuscation, serves as a counterexample to their claim (for the parameterization stated). 2) In our second contribution we show that the DGO construction is actually secure in the ideal permutation model from any trapdoor permutation when parameterized correctly. In particular, when the number of rounds in the construction is equal to \lambda·n·b where \lambda is the security parameter, n is the number of replicas and b is the number of blocks. To do so we build up a proof approach from the ground up that accounts for general attacker storage behavior where we create an analysis technique that we call "sequence-then-switch". 3) Finally, we show a new construction that is provably secure in the random oracle (or random function) model. Thus requiring less structure on the ideal function.