Fully homomorphic encryption (FHE) is a powerful and widely used primitive in lots of real-world applications. Recently, Li and Micciancio [Eurocrypt'21] introduced IND-CPA-D security, which strengthens the standard IND-CPA security by allowing the attacker to access a decryption oracle for honestly generated ciphertexts. Recently, Jung et al. [CCS'24] and Checri et al. [Crypto'24] have shown that even exact FHE schemes like FHEW/TFHE/BGV/BFV may still not be IND-CPA-D secure, by exploiting the bootstrapping failure. However, such attacks can be mitigated by setting negligible bootstrapping failure probability. On the other hand, Liu and Wang [Asiacrypt'24] proposed relaxed functional bootstrapping, which has orders of magnitude performance improvement and furthermore allows a free function evaluation during bootstrapping. These efficiency advantages make it a competitive choice in many applications. In this work, we show that the underlying secret key could be recovered within 10 minutes against all existing relaxed functional bootstrapping constructions, and even within 1 minute for some of them. Moreover, our attack works even with a negligible bootstrapping failure probability. Additionally, we propose a general fix that mitigates all the existing modulus-switching-error-based attacks in the IND-CPA-D model. This is achieved by constructing a new modulus switching procedure with essentially no overhead. Lastly, we show that IND-CPA-D may not be sufficient even for passive adversary model. Thus, we extend this model to IND-CPA-D with randomness (IND-CPA-DR).

Verifiable Computation over encrypted data (VCoed) has two popular paradigms: SNARK-FHE (applying SNARKs to prove FHE operations) and FHE-SNARK (homomorphically evaluating SNARK proofs). For the existing works, FHE-SNARK has a much better efficiency compared to SNARK-FHE.

Rollups are special applications on distributed state machines (aka blockchains) for which the underlying state machine only logs, but does not execute, transactions. Rollups scale throughput by using auxiliary machines that have higher throughput and lower cost of executing transactions than the underlying blockchain. State updates are periodically posted to the underlying blockchain and either verified directly through succinct cryptographic proofs (zk rollups) or can be challenged for a defined period of time in a verifiable way by third parties (optimistic rollups). However, once computation is reduced, communication quickly becomes the new bottleneck. The critical service that the underlying blockchain provides, in addition to verification, is data availability: that necessary data can always be recovered upon request. However, directly broadcasting data requires communication per participant that is linear in the data size. Verifiable information dispersal (VID) systems achieve sublinear blowup in the Ethereum's security and same participation model, where all nodes have a strong public-key identity. However, it is not known how to do so in the permissionless model (the Bitcoin model), where participants are unauthenticated and participation is dynamic. We construct a VID system that is secure under the same model as Bitcoin, with one minimal additional requirement on the existence of reliable participants. Our system uses a state machine replication (SMR) protocol (e.g., Bitcoin) as a black box, and is therefore backward compatible. We implemented the system on top of Bitcoin core with the Regression Test Network (regtest), and our analysis shows that it can reduce communication costs and latency up to more than$1, 000\times$and$10\times$, respectively, for certain parameter choices.

A privacy pool enables clients to deposit units of a cryptocurrency into a shared pool where ownership of deposited currency is tracked via a system of cryptographically hidden records. Clients may later withdraw from the pool without linkage to previous deposits. Some privacy pools also support hidden transfer of currency ownership within the pool. In August 2022, the U.S. Department of Treasury sanctioned Tornado Cash, the largest Ethereum privacy pool, on the premise that it enables illicit actors to hide the origin of funds, citing its usage by the DPRK-sponsored Lazarus Group to launder over $455 million dollars worth of stolen cryptocurrency. This ruling effectively made it illegal for U.S. persons/institutions to use or accept funds that went through Tornado Cash, sparking a global debate among privacy rights activists and lawmakers. Against this backdrop, we present Derecho, a system that institutions could use to request cryptographic attestations of fund origins rather than naively rejecting all funds coming from privacy pools. Derecho is a novel application of proof-carrying data, which allows users to propagate allowlist membership proofs through a privacy pool's transaction graph. Derecho is backwards-compatible with existing Ethereum privacy pool designs, adds no overhead in gas costs, and costs users only a few seconds to produce attestations.

Private Information Retrieval (PIR) is a two player protocol where the client, given some query x ε [N], interacts with the server, which holds a N-bit string DB, in order to privately retrieve DB[x]. In this work, we focus on the single-server client-preprocessing model, initially proposed by Corrigan-Gibbs and Kogan (EUROCRYPT 2020), where the client and server first run a joint preprocessing algorithm, after which the client can retrieve elements from DB privately in time sublinear in N. Most known constructions of single-server client-preprocessing PIR follow one of two paradigms: They feature either (1) a linear-bandwidth offline phase where the client downloads the whole database from the server, or (2) a sublinear-bandwidth offline phase where however the server has to compute a large-depth (Ωλ(N)) circuit under fully-homomorphic encryption (FHE) in order to execute the preprocessing phase.

Verifiable registries allow clients to securely access a key-value mapping maintained by an untrusted server. Registries must be audited to ensure global invariants are preserved, which, in turn, allows for efficient monitoring of individual registry entries by their owners. To this end, existing proposals either assume trusted third-party auditors or rely on incrementally verifiable computation (IVC) via expensive recursive SNARKs to make registries client-auditable.

We present a new primitive supporting file replication in distributed storage networks (DSNs) called a Public Incompressible Encoding (PIE). PIEs operate in the challenging public DSN setting where files must be encoded and decoded with public randomness-i.e., without encryption-and retention of redundant data must be publicly verifiable. They prevent undetectable data compression, allowing DSNs to use monetary rewards or penalties in incentivizing economically rational servers to properly replicate data. Their definition also precludes critical, demonstrated attacks involving parallelism via ASICs and other custom hardware. Our PIE construction is the first to achieve experimentally validated near-optimal performance-within a factor of 4 of optimal by one metric. It also allows decoding orders of magnitude faster than encoding, unlike other comparable constructions. We achieve this high security and performance using a graph construction called a Dagwood Sandwich Graph (DSaG), built from a novel interleaving of depth-robust graphs and superconcentrators. PIEs' performance makes them appealing for DSNs, such as the proposed Filecoin system and Ethereum data sharding. Conversely, their near-optimality establishes concerning bounds on the practical financial and energy costs of DSNs allowing arbitrary data.

Functional encryption (FE) is an extremely powerful cryptographic mechanism that lets an authorized entity compute on encrypted data, and learn the results in the clear. However, all current cryptographic instantiations for general FE are too impractical to be implemented. We construct IRON, a provably secure, and practical FE system using Intel's recent Software Guard Extensions (SGX). We show that IRON can be applied to complex functionalities, and even for simple functions, outperforms the best known cryptographic schemes. We argue security by modeling FE in the context of hardware elements, and prove that IRON satisfies the security model.

The Blind Seer system (Oakland 2014) is an efficient and scalable DBMS that affords both client query privacy and server data protection. It also provides the ability to enforce authorization policies on the system, restricting client's queries while maintaining the privacy of both query and policy. Blind Seer supports a rich query set, including arbitrary boolean formulas, and is provably secure with respect to a controlled amount of search pattern leakage. No other system to date achieves this tradeoff of performance, generality, and provable privacy. A major shortcoming of Blind Seer is its reliance on semi-honest security, particularly for access control and data protection. A malicious client could easily cheat the query authorization policy and obtain any database records satisfying any query of its choice, thus violating basic security features of any standard DBMS. In sum, Blind Seer offers additional privacy to a client, but sacrifices a basic security tenet of DBMS. In the present work, we completely resolve the issue of a malicious client. We show how to achieve robust access control and data protection in Blind Seer with virtually no added cost to performance or privacy. Our approach also involves a novel technique for a semi-private function secure function evaluation (SPF-SFE) that may have independent applications. We fully implement our solution and report on its performance.