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1
Intro
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What is homomorphic encryption?
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Achieving homomorphic encryption
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Applications of homomorphic encryption
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Is homomorphic encryption practical?
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The Learning with Errors problem (LWE)
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LWE parameters
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The Bounded Distance Decoding (BDD) problem
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The Ring-LWE problem
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Security argument for the FV scheme?
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Algorithms for solving LWE
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NIST post-quantum standardisation process
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Estimating NTRU-based schemes in the LWE estimator
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Estimating cost of Lattice reduction
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Implementing the SVP oracle
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Translating asymptotics into concrete cost
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Cost models used in NIST proposal
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Need to ensure correctness of decoding
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Examples: binary and balanced base-B encoding
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Other choices for comparison
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Maximal depth and noise
Description:
Explore the intricacies of Fully Homomorphic Encryption (FHE) in this 45-minute talk by Rachel Player from Sorbonne Université. Delve into the security aspects of lattice-based cryptography, focusing on Ring Learning with Errors (Ring-LWE) problem-based FHE schemes. Examine the selection of secure Ring-LWE parameters and compare differing estimates used in NIST post-quantum cryptography process submissions. Investigate the impact of encoding raw data into plaintext space on efficiency, and learn about a Fan-Vercauteren FHE scheme variant that offers a convenient plaintext space for encoding and enables higher-depth circuit evaluation. Gain insights into topics such as the Learning with Errors problem, Bounded Distance Decoding, security arguments for the FV scheme, algorithms for solving LWE, and the NIST post-quantum standardization process.

Security and Encoding in Fully Homomorphic Encryption - Rachel Player, Sorbonne Université

Alan Turing Institute
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