Learning with Errors (LWE) is a mathematical problem that forms the basis for several advanced cryptographic constructions, particularly in post-quantum cryptography. Its security stems from the computational difficulty of distinguishing between truly random data and data that has been intentionally perturbed with a small error. This problem is considered resistant to attacks by quantum computers, making it suitable for future encryption standards.
Context
In crypto news, Learning with Errors is frequently mentioned when discussing the imperative to upgrade existing cryptographic infrastructure to withstand quantum computing threats. It is a key component of lattice-based cryptography, which is being developed to secure digital asset transactions and communications in a post-quantum era. The ongoing research and standardization efforts around LWE-based schemes are critical for the long-term viability of blockchain technology.
New one-shot signature construction leverages indistinguishability obfuscation, resolving a decade-old cryptographic commitment problem and bolstering post-quantum security.
A novel succinct oblivious tensor evaluation primitive, secured by Learning With Errors, enables adaptively-secure laconic function evaluation and optimal trapdoor hashing, advancing private verifiable computation.
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