Secure Context-sensitive Authorization

Pervasive computing leads to an increased integration between the real world and the computational world, and many applications in pervasive computing adapt to the user\u27s context, such as the location of the user and relevant devices, the presence of other people, light or sound conditions, or available network bandwidth, to meet a user\u27s continuously changing requirements without taking explicit input from the users. We consider a class of applications that wish to consider a user\u27s context when deciding whether to authorize a user\u27s access to important physical or information resources. Such a context-sensitive authorization scheme is necessary when a mobile user moves across multiple administrative domains where they are not registered in advance. Also, users interacting with their environment need a non-intrusive way to access resources, and clues about their context may be useful input into authorization policies for these resources. Existing systems for context-sensitive authorization take a logic-based approach, because a logical language makes it possible to define a context model where a contextual fact is expressed with a boolean predicate and to derive higher-level context information and authorization decisions from contextual facts. However, those existing context-sensitive authorization systems have a central server that collects context information, and evaluates policies to make authorization decisions on behalf of a resource owner. A centralized solution assumes that all resource owners trust the server to make correct decisions, and all users trust the server not to disclose private context information. In many realistic applications of pervasive computing, however, the resources, users, and sources of context information are inherently distributed among many organizations that do not necessarily trust each other. Resource owners may not trust the integrity of context information produced by another domain, and context sensors may not trust others with the confidentiality of data they provide about users. In this thesis, we present a secure distributed proof system for context-sensitive authorization. Our system enables multiple hosts to evaluate an authorization query in a peer-to-peer way, while preserving the confidentiality and integrity policies of mutually untrusted principals running those hosts. We also develop a novel caching and revocation mechanism to support context-sensitive policies that refer to information in dozens of different administrative domains. Contributions of this thesis include the definition of fine-grained security policies that specify trust relations among principals in terms of information confidentiality and integrity, the design and implementation of a secure distributed proof system, a proof for the correctness of our algorithm, and a performance evaluation showing that the amortized performance of our system scales to dozens of servers in different domains