Verifying user attributes to provide fine-grained access control to databases is fundamental to attribute-based authentication. Either a single (central) authority verifies all the attributes, or multiple independent authorities verify the attributes distributedly. In the central setup, the authority verifies all user attributes, and the user downloads only the authorized record. While this is communication efficient, it reveals all user attributes to the authority. A distributed setup prevents this privacy breach by letting each authority verify and learn only one attribute. Motivated by this, Jafarpisheh~et~al. introduced an information-theoretic formulation, called distributed attribute-based private access control (DAPAC). With $N$ non-colluding authorities (servers), $N$ attributes and $K$ possible values for each attribute, the DAPAC system lets each server learn only the single attribute value that it verifies, and is oblivious to the remaining $N-1$. The user retrieves its designated record, without learning anything about the remaining database records. The goal is to maximize the rate, i.e., the ratio of desired message size to total download size. However, not all attributes are sensitive, and DAPAC's privacy constraints can be too restrictive, negatively affecting the rate. To leverage the heterogeneous privacy requirements of user attributes, we propose heterogeneous (Het)DAPAC, a framework which off-loads verification of $N-D$ of the $N$ attributes to a central server, and retains DAPAC's architecture for the $D$ sensitive attributes. We first present a HetDAPAC scheme, which improves the rate from $\frac{1}{2K}$ to $\frac{1}{K+1}$, while sacrificing the privacy of a few non-sensitive attributes. Unlike DAPAC, our scheme entails a download imbalance across servers; we propose a second scheme achieving a balanced per-server download and a rate of $\frac{D+1}{2KD}$.
翻译:验证用户属性以提供细粒度的数据库访问控制是基于属性认证的基础。通常采用单一(中心)机构验证所有属性,或多个独立机构分布式验证属性。在中心化设置中,机构验证所有用户属性,用户仅下载授权记录。这种方式虽通信高效,但会向机构暴露全部用户属性。分布式设置通过让每个机构仅验证并获知单一属性,避免了此类隐私泄露。基于此,Jafarpisheh等人提出了一种信息论框架,称为分布式基于属性的私有访问控制(DAPAC)。在包含N个非共谋机构(服务器)、N个属性且每个属性有K个可能值的系统中,DAPAC使每个服务器仅获知其验证的单个属性值,对其余N-1个属性完全不可知。用户可检索其指定记录,且无法获知数据库中其他记录的信息。该系统的目标是最大化速率,即所需消息大小与总下载大小的比值。然而,并非所有属性均属敏感信息,DAPAC的隐私约束可能过于严格,从而对速率产生负面影响。为适应用户属性的异构隐私需求,我们提出异构(Het)DAPAC框架:将N个属性中的N-D个属性验证任务卸载至中心服务器,并对D个敏感属性保留DAPAC架构。我们首先提出一种HetDAPAC方案,将速率从$\\frac{1}{2K}$提升至$\\frac{1}{K+1}$,同时牺牲少量非敏感属性的隐私。与DAPAC不同,该方案导致服务器间下载负载不均衡;我们进而提出第二种方案,实现服务器间均衡下载,并获得$\\frac{D+1}{2KD}$的速率。