Advancements in Secure Computing and Coding Theory

The field of secure computing and coding theory is rapidly advancing, with a focus on developing innovative solutions to protect data and ensure privacy. Recent research has concentrated on improving the security and efficiency of various cryptographic schemes, including secure coded distributed computation, demand private coded caching, and fully homomorphic encryption. Notably, new constructions and techniques have been proposed to achieve optimal security and efficiency in these areas. Additionally, there has been significant progress in characterizing the optimal memory-rate tradeoff in secure coded caching and secure gradient coding. Some noteworthy papers include: Optimal Secure Coded Distributed Computation over all Fields, which presents optimal secure coded distributed schemes for all fields, and Accurate BGV Parameters Selection, which provides a new method for estimating noise growth in the Brakerski-Gentry-Vaikuntanathan scheme. Overall, these advancements have the potential to significantly impact the development of secure and efficient computing systems.

Sources

Secured Encryption scheme based on the Ree groups

Optimal Secure Coded Distributed Computation over all Fields

Demand Private Coded Caching: Small Cache Size

Secret Sharing in the Rank Metric

Accurate BGV Parameters Selection: Accounting for Secret and Public Key Dependencies in Average-Case Analysis

Characterizing the Optimal Memory-Rate Tradeoff in Secure Coded Caching for Small Buffer or Small Rate

Multi-Message Secure Aggregation with Demand Privacy

On the Optimal Source Key Size of Secure Gradient Coding

Differentially Private Secure Multiplication with Erasures and Adversaries

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