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1. Leibniz International Proceedings in Informatics (LIPIcs):15th Innovations in Theoretical Computer Science Conference (ITCS 2024)

   https://doi.org/10.4230/LIPIcs.ITCS.2024.16  

   Blackwell, Keller; Wootters, Mary (January 2024, Leibniz international proceedings in informatics)

   Guruswami, Venkatesan (Ed.)

   A Homomorphic Secret Sharing (HSS) scheme is a secret-sharing scheme that shares a secret x among s servers, and additionally allows an output client to reconstruct some function f(x), using information that can be locally computed by each server. A key parameter in HSS schemes is download rate, which quantifies how much information the output client needs to download from each server. Recent work (Fosli, Ishai, Kolobov, and Wootters, ITCS 2022) established a fundamental limitation on the download rate of linear HSS schemes for computing low-degree polynomials, and gave an example of HSS schemes that meet this limit. In this paper, we further explore optimal-rate linear HSS schemes for polynomials. Our main result is a complete characterization of such schemes, in terms of a coding-theoretic notion that we introduce, termed optimal labelweight codes. We use this characterization to answer open questions about the amortization required by HSS schemes that achieve optimal download rate. In more detail, the construction of Fosli et al. required amortization over 𝓁 instances of the problem, and only worked for particular values of 𝓁. We show that - perhaps surprisingly - the set of 𝓁’s for which their construction works is in fact nearly optimal, possibly leaving out only one additional value of 𝓁. We show this by using our coding-theoretic characterization to prove a necessary condition on the 𝓁’s admitting optimal-rate linear HSS schemes. We then provide a slightly improved construction of optimal-rate linear HSS schemes, where the set of allowable 𝓁’s is optimal in even more parameter settings. Moreover, based on a connection to the MDS conjecture, we conjecture that our construction is optimal for all parameter regimes. 

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2. All-Norm Load Balancing in Graph Streams via the Multiplicative Weights Update Method

   https://doi.org/10.4230/LIPIcs.ITCS.2023.7  

   Assadi, Sepehr; Bernstein, Aaron; Langley, Zachary (January 2023, Schloss Dagstuhl – Leibniz-Zentrum für Informatik)

   Tauman_Kalai, Yael (Ed.)

   In the weighted load balancing problem, the input is an n-vertex bipartite graph between a set of clients and a set of servers, and each client comes with some nonnegative real weight. The output is an assignment that maps each client to one of its adjacent servers, and the load of a server is then the sum of the weights of the clients assigned to it. The goal is to find an assignment that is well-balanced, typically captured by (approximately) minimizing either the 𝓁_∞- or 𝓁₂-norm of the server loads. Generalizing both of these objectives, the all-norm load balancing problem asks for an assignment that approximately minimizes all 𝓁_p-norm objectives for p ≥ 1, including p = ∞, simultaneously. Our main result is a deterministic O(log n)-pass O(1)-approximation semi-streaming algorithm for the all-norm load balancing problem. Prior to our work, only an O(log n)-pass O(log n)-approximation algorithm for the 𝓁_∞-norm objective was known in the semi-streaming setting. Our algorithm uses a novel application of the multiplicative weights update method to a mixed covering/packing convex program for the all-norm load balancing problem involving an infinite number of constraints. 

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3. High-Threshold AVSS with Optimal Communication Complexity

   AlHaddad, Nicolas; Varia, Mayank; Zhang, Haibin (March 2021, Financial Cryptography and Data Security)

   Asynchronous verifiable secret sharing (AVSS) protocols protect a secret that is distributed among N parties. Dual-threshold AVSS protocols guarantee consensus in the presence of T Byzantine failures and privacy if fewer than P parties attempt to reconstruct the secret. In this work, we construct a dual-threshold AVSS protocol that is optimal along several dimensions. First, it is a high-threshold AVSS scheme, meaning that it is a dual-threshold AVSS with optimal parameters T < N/3 and P < N - T. Second, it has O(N^2) message complexity, and for large secrets it achieves the optimal O(N) communication overhead, without the need for a public key infrastructure or trusted setup. While these properties have been achieved individually before, to our knowledge this is the first protocol that is achieves all of the above simultaneously. The core component of our construction is a high-threshold AVSS scheme for small secrets based on polynomial commitments that achieves O(N^2 log(N)) communication overhead, as compared to prior schemes that require O(N^3) overhead with T 

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4. S ³ ORAM: A Computation-Efficient and Constant Client Bandwidth Blowup ORAM with Shamir Secret Sharing

   https://doi.org/10.1145/3133956.3134090  

   Hoang, Thang; Ozkaptan, Ceyhun D.; Yavuz, Attila A.; Guajardo, Jorge; Nguyen, Tam (November 2017, The ACM Conference on Computer and Communications Security (CCS))

   Oblivious Random Access Machine (ORAM) enables a client to access her data without leaking her access patterns. Existing client-efficient ORAMs either achieve O(log N) client-server communication blowup without heavy computation, or O(1) blowup but with expensive homomorphic encryptions. It has been shown that O(log N) bandwidth blowup might not be practical for certain applications, while schemes with O(1) communication blowup incur even more delay due to costly homomorphic operations. In this paper, we propose a new distributed ORAM scheme referred to as Shamir Secret Sharing ORAM (S3ORAM), which achieves O(1) client-server bandwidth blowup and O(1) blocks of client storage without relying on costly partial homomorphic encryptions. S3ORAM harnesses Shamir Secret Sharing, tree-based ORAM structure and a secure multi-party multiplication protocol to eliminate costly homomorphic operations and, therefore, achieves O(1) clientserver bandwidth blowup with a high computational efficiency. We conducted comprehensive experiments to assess the performance of S3ORAM and its counterparts on actual cloud environments, and showed that S3ORAM achieves three orders of magnitude lower end-to-end delay compared to alternatives with O(1) client communication blowup (Onion-ORAM), while it is one order of magnitude faster than Path-ORAM for a network with a moderate bandwidth quality. We have released the implementation of S3ORAM for further improvement and adaptation. 

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5. One Server for the Price of Two: Simple and Fast Single-Server Private Information Retrieval

   Henzinger, Alexandra; Hong, Matthew M.; Corrigan-Gibbs, Henry; Meiklejohn, Sarah; Vaikuntanathan, Vinod (January 2023, USENIX Security Symposium)

   We present SimplePIR, the fastest single-server private information retrieval scheme known to date. SimplePIR’s security holds under the learning-with-errors assumption. To answer a client’s query, the SimplePIR server performs fewer than one 32-bit multiplication and one 32-bit addition per database byte. SimplePIR achieves 10 GB/s/core server throughput, which approaches the memory bandwidth of the machine and the performance of the fastest two-server private-information-retrieval schemes (which require non-colluding servers). SimplePIR has relatively large communication costs: to make queries to a 1 GB database, the client must download a 121 MB "hint" about the database contents; thereafter, the client may make an unbounded number of queries, each requiring 242 KB of communication. We present a second single-server scheme, DoublePIR, that shrinks the hint to 16 MB at the cost of slightly higher per-query communication (345 KB) and slightly lower throughput (7.4 GB/s/core). Finally, we apply our new private-information-retrieval schemes, together with a novel data structure for approximate set membership, to the task of private auditing in Certificate Transparency. We achieve a strictly stronger notion of privacy than Google Chrome’s current approach with modest communication overheads: 16 MB of download per month, along with 150 bytes per TLS connection. 

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