Efficient privacy preserving content based publish subscribe systems

Abstract

The ability to seamlessly scale on demand has made Content-Based Publish-Subscribe (CBPS) systems the choice of distributing messages/documents produced by Content Publishers to many Subscribers through Content Brokers. Most of the current systems assume that Content Brokers are trusted for the confidentiality of the data published by Content Publishers and the privacy of the subscriptions, which specify their interests, made by Subscribers. However, with the increased use of technologies, such as service oriented architectures and cloud computing, essentially outsourcing the broker functionality to third-party providers, one can no longer assume the trust relationship to hold. The problem of providing privacy/confidentiality in CBPS systems is challenging, since the solution to the problem should allow Content Brokers to make routing decisions based on the content without revealing the content to them. The previous work attempted to solve this problem was not fully successful. The problem may appear unsolvable since it involves conflicting goals, but in this paper, we propose a novel approach to preserve the privacy of the subscriptions made by Subscribers and confidentiality of the data published by Content Publishers using cryptographic techniques when third-party Content Brokers are utilized to make routing decisions based on the content. Our protocols are expressive to support any type of subscriptions and designed to work efficiently. We distribute the work such that the load on Content Brokers, where the bottleneck is in a CBPS system, is minimized. We extend a popular CBPS system using our protocols to implement a privacy preserving CBPS system.