Title: QTM: Trust Management with Quantified Stochastic Attributes


Author: Eric Freudenthal and Vijay Karamcheti 


Trust management systems enable the construction of access-control infrastructures suitable
for protecting sensitive resources from access by unauthorized agents. The  state of the
art in such systems (i) provide fail-safe in that access will be denied when authorizing
credentials are revoked, (ii) can mitigate the risk of insider attacks using mechanisms for
threshold authorization in which several independent partially trusted agents are required
to co-sponsor sensitive activities, and (iii) are capable of enforcing intra- and inter-
organizational access control policies.

Despite these advantages, trust management systems are limited in their ability to express
partial trust. Additionally, they are cumbersome to administer when there are a large
number of related access rights with differing trust (and thereby access) levels due to the
need for explicit enumeration of the exponential number of agent combinations. More
importantly, these systems have no provision for fault tolerance in cases where a primary
authorization is lost (perhaps due to revocation), but others are available. Such
situations may result in a cascading loss of access and possible interruption of service.

In this pape, we propose extending traditional trust management systems through a framework
of reliability and confidence metrics. This framework naturally captures partial trust
relationships, thereby reducing administrative complexity of access control systems with
multiple related trust levels and increasing system availability in the presence of
authorization faults while still maintaining equivalent safety properties.