Differential privacy for collaborative security

Abstract

Fighting global security threats with only a local view is inherently difficult. Internet network operators need to fight global phenomena such as botnets, but they are hampered by the fact that operators can observe only the traffic in their local domains. We propose a collaborative approach to this problem, in which operators share aggregate information about the traffic in their respective domains through an automated query mechanism. We argue that existing work on differential privacy and type systems can be leveraged to build a programmable query mechanism that can express a wide range of queries while limiting what can be learned about individual customers. We report on our progress towards building such a mechanism, and we discuss opportunities and challenges of the collaborative security approach.