Abstract. Publish/subscribe (pub/sub) systems support highly scalable, manyto-many communications among loosely coupled publishers and subscribers. Modern pub/sub systems perform message routing based on the message content and allow subscribers to receive messages related to their subscriptions and the current context. However, both content and context encode sensitive information which should be protected from third-party brokers that make routing decisions. In this work, we address this issue by proposing an approach for constructing a privacy preserving context-based pub/sub system. In particular, our approach assures the confidentiality of the messages being published and subscriptions being issued while allowing the brokers to make routing decisions without decrypting individual messages and subscriptions, and without learning the context. Further, subscribers with a frequently changing context such as location are able to issue and update subscriptions without revealing the subscriptions in plaintext to the broker and without the need to contact a trusted third party for each subscription change resulting from a change in the context. Our approach is based on a modified version of the Paillier additive homomorphic cryptosystem and a recent expressive group key management scheme. The former construct is used to perform privacy preserving matching and covering, and the latter construct is used to enforce fine-grained encryption based access control on the messages being published. We optimize our approach in order to efficiently handle frequently changing contexts. We have implemented our approach in a prototype using an industry strength JMS broker middleware. The experimental results show that our approach is highly practical.
Nabeel et al. REF propose a privacy-preserving contextbased pub/sub system based on a modified Paillier cryptosystem and a group key management scheme.
Privacy Preserving Context Aware Publish Subscribe Systems
Lecture Notes in Computer Science
Lecture Notes in Computer Science
Computer Science