EBElette Boyle
Elette Boyle
*This is an algorithmically generated author record based on publicly available information.
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Elette Boyle has a total of 60 co-authors. Here are the top co-authors by number of shared publications:
- Ran Cohen
Reichman University
9 shared publications - Niv Gilboa
Department of Computer Science Ben-Gurion University of the Negev Israel
7 shared publications - Yuval Ishai
Technion
7 shared publications Niv Gilboa
Ben-Gurion University of the Negev
6 shared publicationsYuval Ishai
Technion—Israel Institute of Technology
6 shared publications- Geoffroy Couteau
Université Paris Cité, CNRS, IRIF
3 shared publications
Latest Publications
- 4 November 2026
- Published by Springer Nature
- p. 132-163
Distributed SNARGs Robust to Corrupt Verifiers
- 27 September 2026
- Published by Springer Nature
- p. 311-329
Topology-Hiding Computation from Key Agreement in Diameter-Two Graphs
- 27 September 2026
- Published by Springer Nature
- p. 311-329
Topology-Hiding Computation from Key Agreement in Diameter-Two Graphs
- Open Access
- 12 August 2026
- Published by Springer Nature
- p. 462-494
Dishonest-Majority Secure Computation via PIR-Authenticated Multiplication Triples
- 12 August 2026
- Published by Springer Nature
- p. 462-494
Open AccessDishonest-Majority Secure Computation via PIR-Authenticated Multiplication Triples
- 12 August 2026
- Published by Springer Nature
- p. 495-526
Fast PCGs for Batch-Authenticated Multiplication Triples
- 12 August 2026
- Published by Springer Nature
- p. 495-526
Fast PCGs for Batch-Authenticated Multiplication Triples
- 6 May 2026
- Published by Springer Nature
- p. 546-572
Maintaining Sublinear Locality Over Time: Adaptively Secure MPC on a Reusable Hidden Graph
- 6 May 2026
- Published by Springer Nature
- p. 546-572
Maintaining Sublinear Locality Over Time: Adaptively Secure MPC on a Reusable Hidden Graph
- 28 April 2025
- Published by Springer Nature
- p. 301-330
The Complexity of Memory Checking with Covert Security
- 28 April 2025
- Published by Springer Nature
- p. 301-330
The Complexity of Memory Checking with Covert Security
- 28 April 2025
- Published by Springer Nature
- p. 207-239
Simultaneous-Message and Succinct Secure Computation
- 28 April 2025
- Published by Springer Nature
- p. 207-239
Simultaneous-Message and Succinct Secure Computation
- Open Access
- 27 March 2025
- Published by Association for Computing Machinery (ACM) in Journal of the ACM
- Vol. 72 (2) , 1-43
Memory Checking Requires Logarithmic Overhead
We study the complexity of memory checkers with computational security and prove the first general tight lower bound. Memory checkers, first introduced over 30 years ago by Blum, Evans, Gemmel, Kannan, and Naor (FOCS ’91, Algorithmica ’94), allow a user to store and maintain a large memory on a remote and unreliable server by using small trusted local storage. The user can issue instructions to the server and after every instruction, obtain either the correct value or a failure (but not an incorrect answer) with high probability. The main complexity measure of interest is the size of the local storage and the number of queries the memory checker makes upon every logical instruction. The most efficient known construction has query complexity \(O(\log n/\log \log n)\) and local space proportional to a computational security parameter, assuming one-way functions, where n is the logical memory size. Dwork, Naor, Rothblum, and Vaikuntanathan (TCC ’09) showed that for a restricted class of “deterministic and non-adaptive” memory checkers, this construction is optimal, up to constant factors. However, going beyond the small class of deterministic and non-adaptive constructions has remained a major open problem. In this work, we fully resolve the complexity of memory checkers by showing that any construction with local space p and query complexity q must satisfy \(\begin{equation*} p \ge \frac{n}{(\log n)^{O(q)}} \;. \end{equation*}\) This implies, as a special case, that \(q\ge \Omega (\log n/\log \log n)\) in any scheme, assuming that \(p\le n^{1-\varepsilon }\) for \(\varepsilon \gt 0\) . The bound applies to any scheme with computational security, completeness \(2/3\) , and inverse polynomial in n soundness (all of which make our lower bound only stronger). We further extend the lower bound to schemes where the read complexity \(q_r\) and write complexity \(q_w\) differ. For instance, we show the tight bound that if \(q_r=O(1)\) and \(p\le n^{1-\varepsilon }\) for \(\varepsilon \gt 0\) , then \(q_w\ge n^{\Omega (1)}\) . This is the first lower bound, for any non-trivial class of constructions, showing a read-write query complexity trade-off. Our proof is via a delicate compression argument showing that a “too good to be true” memory checker can be used to compress random bits of information. We draw inspiration from tools recently developed for lower bounds for relaxed locally decodable codes. However, our proof itself significantly departs from these works, necessitated by the differences between settings.- 27 March 2025
- Published by Association for Computing Machinery (ACM) in Journal of the ACM
- Vol. 72 (2) , 1-43
Open AccessMemory Checking Requires Logarithmic Overhead
We study the complexity of memory checkers with computational security and prove the first general tight lower bound. Memory checkers, first introduced over 30 years ago by Blum, Evans, Gemmel, Kannan, and Naor (FOCS ’91, Algorithmica ’94), allow a user to store and maintain a large memory on a remote and unreliable server by using small trusted local storage. The user can issue instructions to the server and after every instruction, obtain either the correct value or a failure (but not an incorrect answer) with high probability. The main complexity measure of interest is the size of the local storage and the number of queries the memory checker makes upon every logical instruction. The most efficient known construction has query complexity \(O(\log n/\log \log n)\) and local space proportional to a computational security parameter, assuming one-way functions, where n is the logical memory size. Dwork, Naor, Rothblum, and Vaikuntanathan (TCC ’09) showed that for a restricted class of “deterministic and non-adaptive” memory checkers, this construction is optimal, up to constant factors. However, going beyond the small class of deterministic and non-adaptive constructions has remained a major open problem. In this work, we fully resolve the complexity of memory checkers by showing that any construction with local space p and query complexity q must satisfy \(\begin{equation*} p \ge \frac{n}{(\log n)^{O(q)}} \;. \end{equation*}\) This implies, as a special case, that \(q\ge \Omega (\log n/\log \log n)\) in any scheme, assuming that \(p\le n^{1-\varepsilon }\) for \(\varepsilon \gt 0\) . The bound applies to any scheme with computational security, completeness \(2/3\) , and inverse polynomial in n soundness (all of which make our lower bound only stronger). We further extend the lower bound to schemes where the read complexity \(q_r\) and write complexity \(q_w\) differ. For instance, we show the tight bound that if \(q_r=O(1)\) and \(p\le n^{1-\varepsilon }\) for \(\varepsilon \gt 0\) , then \(q_w\ge n^{\Omega (1)}\) . This is the first lower bound, for any non-trivial class of constructions, showing a read-write query complexity trade-off. Our proof is via a delicate compression argument showing that a “too good to be true” memory checker can be used to compress random bits of information. We draw inspiration from tools recently developed for lower bounds for relaxed locally decodable codes. However, our proof itself significantly departs from these works, necessitated by the differences between settings.