• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>IEEE transactions on dependable and secure computing >Sensitivity Analysis for Non-Interactive Differential Privacy: Bounds and Efficient Algorithms
【24h】

Sensitivity Analysis for Non-Interactive Differential Privacy: Bounds and Efficient Algorithms

机译：非交互式差异隐私的敏感性分析：界限和高效算法

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Differential privacy (DP) has gained significant attention lately as the state of the art in privacy protection. It achieves privacy by adding noise to query answers. We study the problem of privately and accurately answering a set of statistical range queries in batch mode (i.e., under non-interactive DP). The noise magnitude in DP depends directly on the sensitivity of a query set, and calculating sensitivity was proven to be NP-hard. Therefore, efficiently bounding the sensitivity of a given query set is still an open research problem. In this work, we propose upper bounds on sensitivity that are tighter than those in previous work. We also propose a formulation to exactly calculate sensitivity for a set of COUNT queries. However, it is impractical to implement these bounds without sophisticated methods. We therefore introduce methods that build a graph model G based on a query set Q, such that implementing the aforementioned bounds can be achieved by solving two well-known clique problems on G. We make use of the literature in solving these clique problems to realize our bounds efficiently. Experimental results show that for query sets with a few hundred queries, it takes only a few seconds to obtain results.
机译：差异隐私（DP）最近在隐私保护中作为最先进的艺术状态。它通过添加噪声来查询答案来实现隐私。我们研究私下和准确地回答一组统计范围查询的问题（即在非交互式DP下）。 DP中的噪声幅度直接取决于查询集的灵敏度，并证明计算灵敏度是NP-HARD。因此，有效地限制给定查询集的灵敏度仍然是一个开放的研究问题。在这项工作中，我们提出了比以前的工作中更紧致的敏感性的上限。我们还提出了一种配方，以精确计算一组计数查询的灵敏度。然而，在没有复杂方法的情况下实现这些界限是不切实际的。因此，我们介绍基于查询集Q构建图形模型G的方法，使得通过解决G的两个众所周知的集团问题，可以实现实施上述界限。我们利用文献来解决这些集团问题以实现这些集团问题我们有效地界。实验结果表明，对于带有几百个查询的查询集，只需几秒钟即可获得结果。

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