Abstract

has played a central role in the design of open distributed systems that span distinct administrative domains. When components of a distributed system can assess the trustworthiness of their peers, they are in a better position to interact with them. There are numerous examples of distributed systems that employ trust inference techniques to regulate the interactions of their components including peer-to-peer file sharing systems, web site and email server reputation services and web search engines. The recent rise in popularity of Online Social Networking (OSN) services has made an additional dimension of trust readily available to system designers: social trust. By social trust, we refer to the trust information embedded in social links as annotated by users of an OSN. This thesis ’ overarching contribution is methods for employing social trust embedded in OSNs to solve two distinct and significant problems in distributed information systems. The first system proposed in this thesis assesses the ability of OSN users to correctly classify online identity assertions. The second system assesses the ability of OSN users to correctly configure devices that classify spamming hosts. In both systems, an OSN user

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