论文标题
Secskyline:通过加密云数据库快速保护隐私的天际线查询
SecSkyline: Fast Privacy-Preserving Skyline Queries over Encrypted Cloud Databases
论文作者
论文摘要
云计算的众所周知的好处刺激了数据库服务外包的普及,可以求助于云以方便地存储和查询数据库。如此流行的趋势是对数据隐私的威胁,因为云获得了可能包含敏感信息(例如医疗或财务数据)的数据库和查询的访问。已经提出了大量的工作来查询加密数据库,该数据库主要集中在安全关键字搜索上。在本文中,我们专注于支持安全的天际线查询处理,而不是加密的外包数据库,在这些数据库中几乎没有完成工作。 Skyline查询是一种高级数据库查询,对于多标准决策系统和应用程序很重要。我们建议Secskyline,这是一个新的系统框架,建造了轻巧的加密图,用于快速保护隐私的天际线查询。 Secskyline雄心勃勃地为外包数据库的内容机密性,查询和结果提供了强大的保护,还针对可能导致间接数据泄漏的数据模式,例如数据点和搜索访问模式之间的优势关系。广泛的实验表明,Secskyline在查询延迟中的最先进基本上优越,最高为813美元$ \ times $。
The well-known benefits of cloud computing have spurred the popularity of database service outsourcing, where one can resort to the cloud to conveniently store and query databases. Coming with such popular trend is the threat to data privacy, as the cloud gains access to the databases and queries which may contain sensitive information, like medical or financial data. A large body of work has been presented for querying encrypted databases, which has been mostly focused on secure keyword search. In this paper, we instead focus on the support for secure skyline query processing over encrypted outsourced databases, where little work has been done. Skyline query is an advanced kind of database query which is important for multi-criteria decision-making systems and applications. We propose SecSkyline, a new system framework building on lightweight cryptography for fast privacy-preserving skyline queries. SecSkyline ambitiously provides strong protection for not only the content confidentiality of the outsourced database, the query, and the result, but also for data patterns that may incur indirect data leakages, such as dominance relationships among data points and search access patterns. Extensive experiments demonstrate that SecSkyline is substantially superior to the state-of-the-art in query latency, with up to 813$\times$ improvement.