PassDB: A password database with strict privacy protocol using 3D Bloom filter

Abstract

A Bloom filter is a probabilistic data structure for approximate membership filtering. It is applied in diverse Network systems to enhance a system’s performance and reduce the memory consumption, for instance, Named-Data Networking, Software-Defined Networks, and Wireless Sensor Networking. Bloom filter consumes a tiny amount of RAM space to store information of large sets of data. On the contrary, the Bloom filter is unexplored in the password database. In this article, we present a novel password management system using the 3-Dimensional Bloom filter (3DBF), called PassDB which features a) low space consumption, b) irrecoverable, c) irreversible, and d) high security and strict privacy. PassDB uses twelve 3DBFs to avoid false positives. In addition, we present extremely high accuracy Bloom filter and the accuracy is 99.99% with false positives of 0.000001882. Moreover, PassDB gives utmost importance to the privacy of a user. Why should anyone be allowed to see the password (e.g., encrypted or raw password) with raw user information? This research question poses a new challenge towards the privacy of a user. This practice exploits the privacy of the users in identity management system. Therefore, PassDB imposes strict privacy for password database, i.e., no one is able to map password with a user ID.