A Range Query Method for Data Access Pattern Protection Based on Uniform Access Frequency Distribution

Jing Yan, Zhao Chang, Ke Cheng, Shuguang Wang
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Abstract

Data encryption is necessary to keep user information secure and private on the cloud. However, adversaries can still learn valuable information about the encrypted data by observing data access patterns. To solve this issue, Oblivious RAMs (ORAMs) are proposed to hide access patterns. However, ORAMs are expensive and not suitable for deployment in a large database. In this work, we propose a range query algorithm while providing data access pattern protection based on uniform access frequency. In the preprocessing, multiple key-value pairs in the database are grouped and stored in each storage module, and we make copies for frequently accessed key-value pairs and also add some dummy key-value pairs on each storage module. In the online query processing, according to the range query length of the received query access request, we visit the specific storage module for the query and obtain the query result. Based on the techniques above, our method makes the uniform distribution of access frequency of data blocks in the database and achieves a security guarantee as strong as the state-of-the-art method. Compared with data queries that do not provide data access pattern protection, the ratio of network communication overhead is constant rather than logarithmic in ORAMs.
基于均匀访问频率分布的数据访问模式保护范围查询方法
数据加密对于保证云上用户信息的安全和隐私是必要的。但是,攻击者仍然可以通过观察数据访问模式来了解有关加密数据的有价值的信息。为了解决这个问题,我们提出了遗忘ram (ORAMs)来隐藏访问模式。然而,oram是昂贵的,不适合部署在大型数据库中。在此工作中,我们提出了一种范围查询算法,同时提供基于统一访问频率的数据访问模式保护。在预处理中,将数据库中的多个键值对分组存储在每个存储模块中,对访问频繁的键值对进行复制,并在每个存储模块上添加一些虚拟的键值对。在在线查询处理中,根据接收到的查询访问请求的范围查询长度,对该查询访问特定的存储模块,获得查询结果。在以上技术的基础上,我们的方法使数据库中数据块的访问频率分布均匀,实现了与目前最先进方法一样强的安全保证。与不提供数据访问模式保护的数据查询相比,网络通信开销的比例在oram中是常数而不是对数。
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