Efficient software implementations of large finite fields GF (2 n ) for secure storage applications

• Published in: ACM transactions on storage Vol. 8; no. 1; pp. 1 - 27
• Main Authors: Luo, Jianqiang, Bowers, Kevin D., Oprea, Alina, Xu, Lihao
• Format: Journal Article
• Language: English
• Published: 01.02.2012
• Subjects: Algorithms; Arithmetic; Computer programs; Cryptography; Decoding; Error correction; Mathematical analysis; Software
• ISSN: 1553-3077; 1553-3093
• DOI: 10.1145/2093139.2093141

Finite fields are widely used in constructing error-correcting codes and cryptographic algorithms. In practice, error-correcting codes use small finite fields to achieve high-throughput encoding and decoding. Conversely, cryptographic systems employ considerably larger finite fields to achieve high levels of security. We focus on developing efficient software implementations of arithmetic operations in reasonably large finite fields as needed by secure storage applications. In this article, we study several arithmetic operation implementations for finite fields ranging from GF (2 32 ) to GF (2 128 ). We implement multiplication and division in these finite fields by making use of precomputed tables in smaller fields, and several techniques of extending smaller field arithmetic into larger field operations. We show that by exploiting known techniques, as well as new optimizations, we are able to efficiently support operations over finite fields of interest. We perform a detailed evaluation of several techniques, and show that we achieve very practical performance for both multiplication and division. Finally, we show how these techniques find applications in the implementation of HAIL, a highly available distributed cloud storage layer. Using the newly implemented arithmetic operations in GF (2 64 ), HAIL improves its performance by a factor of two, while simultaneously providing a higher level of security.