Visible to the public Secure Content-Based Routing Using Intel Software Guard Extensions

TitleSecure Content-Based Routing Using Intel Software Guard Extensions
Publication TypeConference Paper
Year of Publication2016
AuthorsPires, Rafael, Pasin, Marcelo, Felber, Pascal, Fetzer, Christof
Conference NameProceedings of the 17th International Middleware Conference
Conference LocationNew York, NY, USA
ISBN Number978-1-4503-4300-8
KeywordsCollaboration, composability, Content-based routing, deterrence, Human Behavior, Metrics, privacy, pubcrawl, Publish/Subscribe, Resiliency, Router Systems Security, Scalability, security, SGX

Content-based routing (CBR) is a powerful model that supports scalable asynchronous communication among large sets of geographically distributed nodes. Yet, preserving privacy represents a major limitation for the wide adoption of CBR, notably when the routers are located in public clouds. Indeed, a CBR router must see the content of the messages sent by data producers, as well as the filters (or subscriptions) registered by data consumers. This represents a major deterrent for companies for which data is a key asset, as for instance in the case of financial markets or to conduct sensitive business-to-business transactions. While there exists some techniques for privacy-preserving computation, they are either prohibitively slow or too limited to be usable in real systems. In this paper, we follow a different strategy by taking advantage of trusted hardware extensions that have just been introduced in off-the-shelf processors and provide a trusted execution environment. We exploit Intel's new software guard extensions (SGX) to implement a CBR engine in a secure enclave. Thanks to the hardware-based trusted execution environment (TEE), the compute-intensive CBR operations can operate on decrypted data shielded by the enclave and leverage efficient matching algorithms. Extensive experimental evaluation shows that SGX adds only limited overhead to insecure plaintext matching outside secure enclaves while providing much better performance and more powerful filtering capabilities than alternative software-only solutions. To the best of our knowledge, this work is the first to demonstrate the practical benefits of SGX for privacy-preserving CBR.

Citation Keypires_secure_2016