...
首页> 外文期刊>Data & Knowledge Engineering >Impossibility of unconditionally secure scalar products
【24h】

Impossibility of unconditionally secure scalar products

机译:不可能无条件地保护标量产品

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       

摘要

The ability to perform scalar products of two vectors, each known to a different party, is a central problem in privacy preserving data mining and other multi-party computation problems. Ongoing search for both efficient and secure scalar product protocols has revealed that this task is not easy. In this paper we show that, indeed, scalar products can never be made secure in the information theoretical sense. We show that any attempt to make unconditionally secure scalar products will inevitably allow one of the parties to learn the other parties input vector with high probability. On the other hand, we show that under various assumptions, such as the existence of a trusted third party or the difficulty of discrete logarithms, both efficient and secure scalar products do exist. We proposed two new protocols for secure scalar products and compare their performance with existing secure scalar products.
机译:执行两个向量的标量积的能力,每个向量对于不同的参与者都是已知的,这是隐私保护数据挖掘和其他多主体计算问题中的核心问题。对有效和安全的标量产品协议的持续搜索表明,这一任务并不容易。在本文中,我们证明了,从信息理论的意义上说,标量产品的确不可能得到安全保护。我们表明,任何制造无条件安全标量产品的尝试都将不可避免地使各方之一以高概率学习另一方的输入矢量。另一方面,我们表明,在各种假设下,例如存在受信任的第三方或离散对数的难度,确实存在有效和安全的标量产品。我们为安全标量产品提出了两种新协议,并将它们的性能与现有安全标量产品进行比较。

著录项

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