A Privacy Preserving Model for Ownership Indexing in Distributed Storage Systems
Tiejian Luo, Zhu Wang, Xiang Wang · 2014
The indexing technique in distributed object storage system is the crucial part of a large scale application, where the index data structure may be published in many nodes. Here arises a problem on preserving the privacy of the ownership information while supporting queries on item locations with limited index space. Probabilistic data structure, such as the bloom filter which records the location of each item in distributed nodes, is one of the promising solutions. The data structure uses a hashed vector to index items on the nodes. In this paper we propose a Lightweight Bloom filter Array (LBA) indexing model which is compact in size and preserves ownership privacy. To tackle with the problem of examining wrong nodes in the lookup process, we find an optimal storage ratio of the bloom filters and reduce its false positive rate based on the observation of the user’s access behavior in Internet applications. We use experiments to verify our proposed solution. In our experiment, the dataset consists of one billion items distributed in one hundred data nodes. The experiments show that our model can reduce the false checking times and save the index space significantly. 1.