A Composite Privacy Leakage Indicator

This paper proposes a Subjective Logic based composite privacy leakage metric that both takes into account the amount of information leakage and also that information with high entropy in some cases may be considered encrypted. It is furthermore shown both analytically and experimentally that Min-entropy is considered better than Shannon, Renyi or Max entropy for identifying encrypted content for the composite metric. This is in particular useful for implementing privacy-enhanced Intrusion Detection Systems (IDS), where sampled encrypted traffic can be considered to have low risk of revealing sensitive information. The combined metric can be used in a Policy Enforcement Point that acts as a proxy/anonymiser in order to to reduce the leakage of private or sensitive information from the IDS sensors to an outsourced Managed Security Service provider. Although the composite privacy indicator is IDS specific, the authorisation architecture is general, and may also be useful for anonymising or pseusonymising sensitive information from or to other types of sensors that need to be exposed to the Internet. The solution is based on the eXtensible Access Control Markup Language policy language extended with support for Subjective Logic, in order to provide a method for expressing fine-grained access control policies that are based on uncertain evidences.