首页> 外文期刊>Designs, Codes and Crytography >On the complexity of the BKW algorithm on LWE
【24h】

On the complexity of the BKW algorithm on LWE

机译:关于LWE上BKW算法的复杂性

获取原文
获取原文并翻译 | 示例
       

摘要

This work presents a study of the complexity of the Blum-Kalai-Wasserman (BKW) algorithm when applied to the Learning with Errors (LWE) problem, by providing refined estimates for the data and computational effort requirements for solving concrete instances of the LWE problem. We apply this refined analysis to suggested parameters for various LWE-based cryptographic schemes from the literature and compare with alternative approaches based on lattice reduction. As a result, we provide new upper bounds for the concrete hardness of these LWE-based schemes. Rather surprisingly, it appears that BKW algorithm outperforms known estimates for lattice reduction algorithms starting in dimension n ≈ 250 when LWE is reduced to SIS. However, this assumes access to an unbounded number of LWE samples.
机译:这项工作通过为解决LWE问题的具体实例提供数据和计算工作量要求的精确估计,研究了Blum-Kalai-Wasserman(BKW)算法在应用于学习错误(LWE)问题时的复杂性。 。我们根据文献对各种基于LWE的密码方案的建议参数应用了这种改进的分析,并与基于晶格约简的替代方法进行了比较。因此,我们为这些基于LWE的方案的混凝土硬度提供了新的上限。出乎意料的是,当将LWE简化为SIS时,从尺寸n≈250开始,BKW算法的性能优于已知的网格约简算法估计。但是,这假设可以访问无限数量的LWE样本。

著录项

  • 来源
    《Designs, Codes and Crytography》 |2015年第2期|325-354|共30页
  • 作者单位

    Technical University of Denmark, Lyngby, Denmark;

    Information Security Group, Royal Holloway, University of London, Egham, Surrey TW20 0EX, UK;

    POLSYS Project, Paris-Rocquencourt Center, INRIA, 75005 Paris, France,LIP6, UMR 7606, UPMC Univ Paris 06,75005 Paris, France,LIP6, UMR 7606, CNRS, 75005 Paris, France;

    Information Security Group, Royal Holloway, University of London, Egham, Surrey TW20 0EX, UK;

    POLSYS Project, Paris-Rocquencourt Center, INRIA, 75005 Paris, France,LIP6, UMR 7606, UPMC Univ Paris 06,75005 Paris, France,LIP6, UMR 7606, CNRS, 75005 Paris, France;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Learning with errors; BKW; LPN; FHE;

    机译:有错误的学习;宝马;LPN;FHE;

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号