VLWE: Variety-based Learning with Errors for Vector Encryption through Algebraic Geometry

• URL: http://arxiv.org/abs/2502.07284v1
• Date: Tue, 11 Feb 2025 06:04:24 GMT
• Title: VLWE: Variety-based Learning with Errors for Vector Encryption through Algebraic Geometry
• Authors: Dongfang Zhao,
• Abstract summary: Lattice-based cryptography is a foundation for post-quantum security. This work introduces Variety-LWE (VLWE), a new structured lattice problem based on algebraic geometry. We prove VLWE's security by reducing it to multiple independent instances, demonstrating resilience against classical and quantum attacks.
• Score: 1.3824176915623292
• License:
• Abstract: Lattice-based cryptography is a foundation for post-quantum security, with the Learning with Errors (LWE) problem as a core component in key exchange, encryption, and homomorphic computation. Structured variants like Ring-LWE (RLWE) and Module-LWE (MLWE) improve efficiency using polynomial rings but remain constrained by traditional polynomial multiplication rules, limiting their ability to handle structured vectorized data. This work introduces Variety-LWE (VLWE), a new structured lattice problem based on algebraic geometry. Unlike RLWE and MLWE, which use polynomial quotient rings with standard multiplication, VLWE operates over multivariate polynomial rings defined by algebraic varieties. A key difference is that these polynomials lack mixed variables, and multiplication is coordinate-wise rather than following standard polynomial multiplication. This enables direct encoding and homomorphic processing of high-dimensional data while preserving worst-case to average-case hardness reductions. We prove VLWE's security by reducing it to multiple independent Ideal-SVP instances, demonstrating resilience against classical and quantum attacks. Additionally, we analyze hybrid algebraic-lattice attacks, showing that existing Grobner basis and lattice reduction methods do not directly threaten VLWE. We further construct a vector homomorphic encryption scheme based on VLWE, supporting structured computations while controlling noise growth. This scheme offers advantages in privacy-preserving machine learning, encrypted search, and secure computations over structured data. VLWE emerges as a novel and independent paradigm in lattice-based cryptography, leveraging algebraic geometry to enable new cryptographic capabilities beyond traditional polynomial quotient rings.

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