Privacy-Preserving Techniques and System for Streaming Databases

• Published in: 2012 International Conference on Privacy, Security, Risk and Trust and 2012 International Confernece on Social Computing pp. 728 - 733
• Main Authors: Santana de Oliveira, Anderson, Kerschbaum, F., Hoon Wei Lim, Su-Yang Yu
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01-09-2012
• Subjects: Bloom filters; Computational efficiency; Correlation; Data privacy; Encryption; Engines; order-preserving encryption; privacy-preserving correlation; streaming databases
• ISBN: 1467356387; 9781467356381
• DOI: 10.1109/SocialCom-PASSAT.2012.85

Streaming databases and other distributed, event-based systems are very useful tools for business and security applications. When event sources and event processing are distributed across multiple distinct domains, confidentiality and privacy issues emerge. These can be addressed by a number of cryptographic techniques. In this paper we consider high-performance symmetric encryption techniques. We build a system for privacy-preserving event correlation and evaluate the performance of the its techniques. We demonstrate efficient privacy-preserving event correlation using equality tests, greater-than comparisons and range queries. The results indicate that in comparable settings, it is therefore recommended to employ these techniques to address pertinent security and privacy concerns.