Privacy-Preserving Filtering and Covering in Content-Based Publish Subscribe Systems

Content-Based Publish-Subscribe (CBPS) is an asynchronous messaging paradigm that supports a highly dynamic and many-to-many communication pattern based on the content of the messages themselves. In general, a CBPS system has three distinct parties Content Publishers , Content Brokers, and Subscribers working in a highly decoupled fashion. The ability to seamlessly scale on demand has made 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 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. We analyze the security of our approach to show that it is indeed sound and provide experimental results to show that it is practical.