Cryptographic Constructions for Secure, Privacy-Preserving Distributed Information Sharing (Seaglass)
Dawn Song, John Bethencourt and Elaine Shi
National Science Foundation and NDSEG Fellowship
A huge volume of data is collected and stored by various sensors, monitoring systems, and auditing systems. Such data often contains sensitive or private information. How can we enable effective distributed information sharing and decision making in a secure and privacy-preserving manner?
The Seaglass project aims to design and develop novel cryptographic constructions to enable secure, privacy-preserving distributed information sharing. The project has employed techniques based on computation of encrypted data to ensure privacy [1-4] and has also developed secure methods for information aggregation [5,6].
- E. Shi, J. Bethencourt, H. Chan, D. Song, and A. Perrig, "Multi-Dimensional Range Query over Encrypted Data," IEEE Symposium on Security and Privacy, 2007.
- J. Bethencourt, D. Song, and B. Waters, "New Constructions and Practical Applications for Private Stream Searching (Extended Abstract)," IEEE Symposium on Security and Privacy, 2006.
- L. Kissner and D. Song, "Privacy Preserving Set Operations," CRYPTO, 2005.
- D. Song, D. Wagner, and A. Perrig, "Practical Techniques for Searches on Encrypted Data," IEEE Symposium on Security and Privacy, 2000.
- H. Chan, A. Perrig, and D. Song, "Secure Hierarchical In-Network Aggregation in Sensor Networks," ACM CCS, 2006.
- B. Przydatek, D. Song, and A. Perrig, "SIA: Secure Information Aggregation in Sensor Networks," ACM SenSys, 2003.