Demo Data from SIGIR 2026 / reviewers in the wild / expert
Aarushi Goel
dblp:172/0408
· DBLP profile ↗
29ranked-venue papers
8as first author
24since 2021 · last 2026
0000-0002-8903-6354ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Security and privacy · 28 · 8 first-author · 23 since 2021Theory of computation · 4 · 1 first-author · 4 since 2021Systems, architecture and hardware · 1 · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Network and information security
21 papers |
Cryptographic protocols and secure computation · 77% Blockchain and cryptocurrency security · 13% Authentication and access control · 3% | |
| Computer architecture, parallel and distributed computing, and storage systems
3 papers |
Distributed systems · 94% Cloud and datacenter computing · 6% |
Topics — the 28 heaviest of 28, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Cryptographic protocols and secure computation
secure multiparty computation |
4.6 | 10 | 2024 | Perfect MPC over Layered Graphs · CRYPTO (1) 2023 Scalable Multiparty Garbling · CCS 2023 Secure Multiparty Computation with Free Branching · EUROCRYPT (1) 2022 |
Cryptographic protocols and secure computation › proof systems
zero-knowledge proofs |
4.4 | 6 | 2025 | Malicious Security in Collaborative zk-SNARKs: More than Meets the Eye · CRYPTO (7) 2025 How to Prove Statements Obliviously? · CRYPTO (10) 2024 Dora: A Simple Approach to Zero-Knowledge for RAM Programs · CCS 2024 |
Distributed systems › consensus
byzantine agreement |
1.3 | 2 | 2024 | Breaking the $O(\sqrt{n})$-Bit Barrier: Byzantine Agreement with Polylog Bits Per Party · J. Cryptol. 2024 Breaking the O(√ n)-Bit Barrier: Byzantine Agreement with Polylog Bits Per Party · PODC 2021 |
Blockchain and cryptocurrency security › smart contract
privacy-preserving smart contracts |
1.0 | 1 | 2026 | Jigsaw: Doubly Private Smart Contracts · SP 2026 |
Blockchain and cryptocurrency security › smart contract
private smart contracts |
1.0 | 1 | 2026 | Jigsaw: Doubly Private Smart Contracts · SP 2026 |
Blockchain and cryptocurrency security
smart contract |
1.0 | 1 | 2026 | Jigsaw: Doubly Private Smart Contracts · SP 2026 |
Cryptographic protocols and secure computation
malicious security |
1.0 | 2 | 2025 | Malicious Security in Collaborative zk-SNARKs: More than Meets the Eye · CRYPTO (7) 2025 Two Round Information-Theoretic MPC with Malicious Security · EUROCRYPT (2) 2019 |
Cryptographic protocols and secure computation › function secret sharing
distributed point function |
0.9 | 1 | 2025 | Multiparty Distributed Point Functions · CRYPTO (4) 2025 |
Cryptographic protocols and secure computation › proof systems › zero-knowledge proofs › non-interactive zero-knowledge proofs
zk-SNARK |
0.9 | 1 | 2025 | Malicious Security in Collaborative zk-SNARKs: More than Meets the Eye · CRYPTO (7) 2025 |
Cryptographic protocols and secure computation
proof systems |
0.8 | 1 | 2024 | Dora: A Simple Approach to Zero-Knowledge for RAM Programs · CCS 2024 |
Distributed systems
consensus |
0.8 | 1 | 2024 | Breaking the $O(\sqrt{n})$-Bit Barrier: Byzantine Agreement with Polylog Bits Per Party · J. Cryptol. 2024 |
Cryptographic protocols and secure computation › garbled circuits
multiparty garbling |
0.7 | 1 | 2023 | Scalable Multiparty Garbling · CCS 2023 |
Cryptographic protocols and secure computation › secure multiparty computation
perfect security |
0.7 | 1 | 2023 | Perfect MPC over Layered Graphs · CRYPTO (1) 2023 |
Privacy and data protection
privacy-preserving machine learning |
0.7 | 1 | 2023 | Experimenting with Zero-Knowledge Proofs of Training · CCS 2023 |
Security and privacy of machine learning › verifiable machine learning
proof of learning |
0.7 | 1 | 2023 | Experimenting with Zero-Knowledge Proofs of Training · CCS 2023 |
Cryptographic protocols and secure computation › proof systems › zero-knowledge proofs
zero-knowledge proof of training |
0.7 | 1 | 2023 | Experimenting with Zero-Knowledge Proofs of Training · CCS 2023 |
Cryptographic protocols and secure computation › interactive proofs
sigma protocols |
0.6 | 1 | 2022 | Stacking Sigmas: A Framework to Compose $\varSigma $-Protocols for Disjunctions · EUROCRYPT (2) 2022 |
Distributed systems › fault tolerance
byzantine fault tolerance |
0.5 | 1 | 2021 | Breaking the O(√ n)-Bit Barrier: Byzantine Agreement with Polylog Bits Per Party · PODC 2021 |
Distributed systems
communication complexity |
0.5 | 1 | 2021 | Breaking the O(√ n)-Bit Barrier: Byzantine Agreement with Polylog Bits Per Party · PODC 2021 |
Cryptographic protocols and secure computation › secure multiparty computation
round complexity |
0.4 | 1 | 2020 | Towards Efficiency-Preserving Round Compression in MPC - Do Fewer Rounds Mean More Computation? · ASIACRYPT (3) 2020 |
Cryptographic protocols and secure computation
communication complexity |
0.4 | 1 | 2019 | The Broadcast Message Complexity of Secure Multiparty Computation · ASIACRYPT (1) 2019 |
Authentication and access control › password authentication
honeywords |
0.4 | 1 | 2019 | Generation of Secure and Reliable Honeywords, Preventing False Detection · IEEE Trans. Dependable Secur. Comput. 2019 |
Authentication and access control
password authentication |
0.4 | 1 | 2019 | Generation of Secure and Reliable Honeywords, Preventing False Detection · IEEE Trans. Dependable Secur. Comput. 2019 |
Cryptographic protocols and secure computation › secure multiparty computation › round complexity
two-round MPC |
0.4 | 1 | 2019 | Two Round Information-Theoretic MPC with Malicious Security · EUROCRYPT (2) 2019 |
Cryptographic protocols and secure computation › secure multiparty computation
unconditionally secure multiparty computation |
0.4 | 1 | 2019 | Two Round Information-Theoretic MPC with Malicious Security · EUROCRYPT (2) 2019 |
Cryptographic protocols and secure computation › secure multiparty computation
honest-majority MPC |
0.3 | 1 | 2018 | Round-Optimal Secure Multiparty Computation with Honest Majority · CRYPTO (2) 2018 |
Cryptographic protocols and secure computation › secure multiparty computation › round complexity
round-optimal protocols |
0.3 | 1 | 2018 | Round-Optimal Secure Multiparty Computation with Honest Majority · CRYPTO (2) 2018 |
Cloud and datacenter computing
secure outsourcing |
0.2 | 1 | 2023 | zkSaaS: Zero-Knowledge SNARKs as a Service · USENIX Security Symposium 2023 |
Methods — techniques the papers use, named apart from their topics
zero-knowledge proofs · 1.3SNARKs · 1.3communication-efficient protocol · 1.0RAM program verification · 0.8zk-SNARK · 0.7learning parity with noise · 0.7MPC-in-the-head · 0.7experimental analysis · 0.4clustering · 0.4broadcast message complexity · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | Weighted Cryptography with Weight-Independent Complexity
Aarushi Goel, Swagata Sasmal, Mingyuan Wang 0001 |
CRYPTO (2) | 1 |
| 2026 | Jigsaw: Doubly Private Smart Contracts
Sanjam Garg, Aarushi Goel, Dimitris Kolonelos, Rohit Sinha 0001 |
SP | 2 |
| 2025 | Malicious Security in Collaborative zk-SNARKs: More than Meets the Eye
Sanjam Garg, Aarushi Goel, Abhishek Jain 0002, Bhaskar Roberts, Sruthi Sekar |
CRYPTO (7) | 2 |
| 2025 | Multiparty Distributed Point Functions
Aarushi Goel, Mingyuan Wang 0001 |
CRYPTO (4) | 1 |
| 2025 | Split Prover Zero-Knowledge SNARKs
Sanjam Garg, Aarushi Goel, Dimitris Kolonelos, Sina Shiehian, Rohit Sinha 0001 |
PKC (1) | 2 |
| 2024 | Dora: A Simple Approach to Zero-Knowledge for RAM ProgramsabstractExisting protocols for proving the correct execution of a RAM program in zero-knowledge are plagued by a processor expressiveness tradeoff: supporting fewer instructions results in smaller processor circuits (which improves performance), but may result in more program execution steps because non-supported instruction must be emulated over multiple processor steps (diminishing performance). Aarushi Goel, Mathias Hall-Andersen, Gabriel Kaptchuk |
CCS | 1 |
| 2024 | How to Prove Statements Obliviously?
Sanjam Garg, Aarushi Goel, Mingyuan Wang 0001 |
CRYPTO (10) | 2 |
| 2024 | Homomorphic Secret Sharing with Verifiable Evaluation
Arka Rai Choudhuri, Aarushi Goel, Aditya Hegde 0003, Abhishek Jain 0002 |
TCC (4) | 2 |
| 2024 | Breaking the $O(\sqrt{n})$-Bit Barrier: Byzantine Agreement with Polylog Bits Per Party
Elette Boyle, Ran Cohen, Aarushi Goel |
J. Cryptol. | 3 |
| 2024 | SublonK: Sublinear Prover PlonKabstractWe propose SublonK --- a new succinct non-interactive argument of knowledge (SNARK). SublonK is the first SNARK that achieves both a constant proof size and prover runtime that grows only with the size of the ``active part'' of the executed circuit (i.e., *sub-linear* in the size of the entire circuit) while being *black-box in cryptography*. For instance, consider circuits encoding conditional execution, where only a fraction of the circuit is exercised by the input. For such circuits, the prover runtime in SublonK grows only with the exercised execution path. Our new construction builds on PlonK [Gabizon-Williamson-Ciobotaru, EPRINT'19], a popular state-of-the-art practical zkSNARK, and preserves all its great features --- constant size proofs, constant time proof verification, a circuit-independent universal setup, and support for custom gates and lookup gates. Our techniques are useful for a wide range of applications that involve a circuit executing k steps, where at each step, a (possibly different) s-sized segment is executed from a choice of n segments. Our prover cost for such circuits is O(ks(log (ks) + log(n))). Finally, we show that our improvements are not purely asymptotic. Specifically, we demonstrate the concrete efficiency of SublonK using zkRollups as an example application. Based on our implementation, for parameter choices derived from rollup contracts on Ethereum, n =8, k = 128, s= 2^{16}, the SublonK prover is approximately 4.8x faster than the PlonK prover, and proofs in SublonK are 2.4KB and can be verified in under 50ms. Arka Rai Choudhuri, Sanjam Garg, Aarushi Goel, Sruthi Sekar, Rohit Sinha 0001 |
Proc. Priv. Enhancing Technol. | 3 |
| 2023 | Scalable Multiparty GarblingabstractMultiparty garbling is the most popular approach for constant-round secure multiparty computation (MPC). Despite being the focus of significant research effort, instantiating prior approaches to multiparty garbling results in constant-round MPC that can not realistically accommodate large numbers of parties. In this work we present the first global-scale multiparty garbling protocol. The per-party communication complexity of our protocol decreases as the number of parties participating in the protocol increases - for the first time matching the asymptotic communication complexity of non-constant round MPC protocols. Our protocol achieves malicious security in the honest-majority setting and relies on the hardness of the Learning Party with Noise assumption. Gabrielle Beck, Aarushi Goel, Aditya Hegde 0003, Abhishek Jain 0002, Zhengzhong Jin, Gabriel Kaptchuk |
CCS | 2 |
| 2023 | Experimenting with Zero-Knowledge Proofs of TrainingabstractHow can a model owner prove they trained their model according to the correct specification? More importantly, how can they do so while preserving the privacy of the underlying dataset and the final model? We study this problem and formulate the notion of zero-knowledge proof of training (zkPoT), which formalizes rigorous security guarantees that should be achieved by a privacy-preserving proof of training. While it is theoretically possible to design zkPoT for any model using generic zero-knowledge proof systems, this approach results in extremely unpractical proof generation times. Towards designing a practical solution, we propose the idea of combining techniques from MPC-in-the-head and zkSNARKs literature to strike an appropriate trade-off between proof size and proof computation time. We instantiate this idea and propose a concretely efficient, novel zkPoT protocol for logistic regression. Sanjam Garg, Aarushi Goel, Somesh Jha, Saeed Mahloujifar, Mohammad Mahmoody, Guru-Vamsi Policharla, Mingyuan Wang 0001 |
CCS | 2 |
| 2023 | Perfect MPC over Layered Graphs
Bernardo Machado David, Giovanni Deligios, Aarushi Goel, Yuval Ishai, Anders Konring, Eyal Kushilevitz, Chen-Da Liu-Zhang, Varun Narayanan |
CRYPTO (1) | 3 |
| 2023 | Speed-Stacking: Fast Sublinear Zero-Knowledge Proofs for Disjunctions
Aarushi Goel, Mathias Hall-Andersen, Gabriel Kaptchuk, Nicholas Spooner |
EUROCRYPT (2) | 1 |
| 2023 | zkSaaS: Zero-Knowledge SNARKs as a Service
Sanjam Garg, Aarushi Goel, Abhishek Jain 0002, Guru-Vamsi Policharla, Sruthi Sekar |
USENIX Security Symposium | 2 |
| 2022 | Stacking Sigmas: A Framework to Compose $\varSigma $-Protocols for Disjunctions
Aarushi Goel, Matthew Green 0001, Mathias Hall-Andersen, Gabriel Kaptchuk |
EUROCRYPT (2) | 1 |
| 2022 | Secure Multiparty Computation with Free Branching
Aarushi Goel, Mathias Hall-Andersen, Aditya Hegde 0003, Abhishek Jain 0002 |
EUROCRYPT (1) | 1 |
| 2022 | One-Time Programs from Commodity Hardware
Harry Eldridge, Aarushi Goel, Matthew Green 0001, Abhishek Jain 0002, Maximilian Zinkus |
TCC (3) | 2 |
| 2022 | Efficient Set Membership Proofs using MPC-in-the-HeadabstractAbstract Set membership proofs are an invaluable part of privacy preserving systems. These proofs allow a prover to demonstrate knowledge of a witness w corresponding to a secret element x of a public set, such that they jointly satisfy a given NP relation, i.e. ℛ(w, x) = 1 and x is a member of a public set {x 1, . . . , x𝓁}. This allows the identity of the prover to remain hidden, eg. ring signatures and confidential transactions in cryptocurrencies. In this work, we develop a new technique for efficiently adding logarithmic-sized set membership proofs to any MPC-in-the-head based zero-knowledge protocol (Ishai et al. [STOC’07]). We integrate our technique into an open source implementation of the state-of-the-art, post quantum secure zero-knowledge protocol of Katz et al. [CCS’18].We find that using our techniques to construct ring signatures results in signatures (based only on symmetric key primitives) that are between 5 and 10 times smaller than state-of-the-art techniques based on the same assumptions. We also show that our techniques can be used to efficiently construct post-quantum secure RingCT from only symmetric key primitives. Aarushi Goel, Matthew Green 0001, Mathias Hall-Andersen, Gabriel Kaptchuk |
Proc. Priv. Enhancing Technol. | 1 |
| 2021 | Fluid MPC: Secure Multiparty Computation with Dynamic Participants
Arka Rai Choudhuri, Aarushi Goel, Matthew Green 0001, Abhishek Jain 0002, Gabriel Kaptchuk |
CRYPTO (2) | 2 |
| 2021 | Order-C Secure Multiparty Computation for Highly Repetitive Circuits
Gabrielle Beck, Aarushi Goel, Abhishek Jain 0002, Gabriel Kaptchuk |
EUROCRYPT (2) | 2 |
| 2021 | Breaking the O(√ n)-Bit Barrier: Byzantine Agreement with Polylog Bits Per PartyabstractByzantine agreement (BA), the task of n parties to agree on one of their input bits in the face of malicious agents, is a powerful primitive that lies at the core of a vast range of distributed protocols. Interestingly, in BA protocols with the best overall communication, the demands of the parties are highly unbalanced: the amortized cost is Õ(1) bits per party, but some parties must send Ω(n) bits. In best known balanced protocols, the overall communication is sub-optimal, with each party communicating Õ(√n). Elette Boyle, Ran Cohen, Aarushi Goel |
PODC | 3 |
| 2021 | On Actively-Secure Elementary MPC Reductions
Benny Applebaum, Aarushi Goel |
TCC (1) | 2 |
| 2021 | On Communication Models and Best-Achievable Security in Two-Round MPC
Aarushi Goel, Abhishek Jain 0002, Manoj Prabhakaran 0001, Rajeev Raghunath |
TCC (2) | 1 |
| 2020 | Towards Efficiency-Preserving Round Compression in MPC - Do Fewer Rounds Mean More Computation?
Prabhanjan Vijendra Ananth, Arka Rai Choudhuri, Aarushi Goel, Abhishek Jain 0002 |
ASIACRYPT (3) | 3 |
| 2019 | The Broadcast Message Complexity of Secure Multiparty Computation
Sanjam Garg, Aarushi Goel, Abhishek Jain 0002 |
ASIACRYPT (1) | 2 |
| 2019 | Two Round Information-Theoretic MPC with Malicious Security
Prabhanjan Vijendra Ananth, Arka Rai Choudhuri, Aarushi Goel, Abhishek Jain 0002 |
EUROCRYPT (2) | 3 |
| 2019 | Generation of Secure and Reliable Honeywords, Preventing False DetectionabstractBreach in password databases has been a frequent phenomena in the software industry. Often these breaches go undetected for years. Sometimes, even the companies involved are not aware of the breach. Even after they are detected, publicizing such attacks might not always be in the best interest of the companies. This calls for a strong breach detection mechanism. Juels et al. (in ACM-CCS 2013) suggest a method called ‘Honeywords’, for detecting password database breaches. Their idea is to generate multiple fake passwords, called honeywords and store them along with the real password. Any login attempt with honeywords is identified as a compromise of the password database, since legitimate users are not expected to know the honeywords corresponding to their passwords. The key components of their idea are (i) generation of honeywords, (ii) typo-safety measures for preventing false alarms, (iii) alarm policy upon detection, and (iv) testing robustness of the system against various attacks. In this work, we analyze the limitations of existing honeyword generation techniques. We propose a new attack model called ‘Multiple System Intersection attack considering Input’. We show that the ‘Paired Distance Protocol’ proposed by Chakraborty et al., is not secure in this attack model. We also propose new and more practical honeyword generation techniques and call them the ‘evolving-password model’, the ‘user-profile model’, and the ‘append-secret model’. These techniques achieve ‘approximate flatness’, implying that the honeywords generated using these techniques are indistinguishable from passwords with high probability. Our proposed techniques overcome most of the risks and limitations associated with existing techniques. We prove flatness of our ‘evolving-password model’ technique through experimental analysis. We provide a comparison of our proposed models with the existing ones under various attack models to justify our claims. Akshima, Donghoon Chang, Aarushi Goel, Sweta Mishra, Somitra Kumar Sanadhya |
IEEE Trans. Dependable Secur. Comput. | 3 |
| 2018 | Round-Optimal Secure Multiparty Computation with Honest Majority
Prabhanjan Vijendra Ananth, Arka Rai Choudhuri, Aarushi Goel, Abhishek Jain 0002 |
CRYPTO (2) | 3 |