...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Knowledge and Data Engineering, IEEE Transactions on >Secure kNN Query Processing in Untrusted Cloud Environments
【24h】

Secure kNN Query Processing in Untrusted Cloud Environments

机译：不受信任的云环境中的安全kNN查询处理

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

Mobile devices with geo-positioning capabilities (e.g., GPS) enable users to access information that is relevant to their present location. Users are interested in querying about points of interest (POI) in their physical proximity, such as restaurants, cafes, ongoing events, etc. Entities specialized in various areas of interest (e.g., certain niche directions in arts, entertainment, travel) gather large amounts of geo-tagged data that appeal to subscribed users. Such data may be sensitive due to their contents. Furthermore, keeping such information up-to-date and relevant to the users is not an easy task, so the owners of such data sets will make the data accessible only to paying customers. Users send their current location as the query parameter, and wish to receive as result the nearest POIs, i.e., nearest-neighbors (NNs). But typical data owners do not have the technical means to support processing queries on a large scale, so they outsource data storage and querying to a cloud service provider. Many such cloud providers exist who offer powerful storage and computational infrastructures at low cost. However, cloud providers are not fully trusted, and typically behave in an honest-but-curious fashion. Specifically, they follow the protocol to answer queries correctly, but they also collect the locations of the POIs and the subscribers for other purposes. Leakage of POI locations can lead to privacy breaches as well as financial losses to the data owners, for whom the POI data set is an important source of revenue. Disclosure of user locations leads to privacy violations and may deter subscribers from using the service altogether. In this paper, we propose a family of techniques that allow processing of NN queries in an untrusted outsourced environment, while at the same time protecting both the POI and querying users’ positions. Our techniques rely on mutable order preserving encoding (mOPE), the only secure order-preserving encryption method known to-- ate. We also provide performance optimizations to decrease the computational cost inherent to processing on encrypted data, and we consider the case of incrementally updating data sets. We present an extensive performance evaluation of our techniques to illustrate their viability in practice.
机译：具有地理位置定位功能的移动设备（例如GPS）使用户能够访问与其当前位置相关的信息。用户有兴趣查询其附近的兴趣点（POI），例如餐馆，咖啡馆，正在进行的活动等。专门从事各个兴趣领域的实体（例如，艺术，娱乐，旅行中的某些特定领域）吸引订阅用户的带有地理标记的数据量。由于其内容，此类数据可能很敏感。此外，保持此类信息最新并与用户相关并非易事，因此此类数据集的所有者将使数据仅对付费客户可用。用户发送其当前位置作为查询参数，并希望接收结果作为最近的POI，即最近的邻居（NN）。但是，典型的数据所有者不具备支持大规模处理查询的技术手段，因此他们将数据存储和查询外包给了云服务提供商。存在许多这样的云提供商，它们以低成本提供强大的存储和计算基础架构。但是，云提供商并未得到完全信任，并且通常以诚实但好奇的方式行事。具体来说，他们遵循协议正确回答查询，但是他们也收集POI和订户的位置以用于其他目的。 POI位置泄漏可能会导致隐私泄露，并给数据所有者带来经济损失，对于这些所有者而言，POI数据集是重要的收入来源。公开用户位置会导致侵犯隐私权，并可能阻止订户完全使用该服务。在本文中，我们提出了一系列技术，这些技术允许在不受信任的外包环境中处理NN查询，同时保护POI和查询用户的位置。我们的技术依靠可变顺序保留编码（mOPE），这是已知的唯一安全的顺序保留加密方法。我们还提供性能优化以减少处理加密数据所固有的计算成本，并且考虑增量更新数据集的情况。我们对我们的技术进行了广泛的性能评估，以说明它们在实践中的可行性。

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