In pervasive computing environments, personal information is typically expressed in digital forms. Daily activities and personal preferences with regard to pervasive computing applications are easily associated with personal identities. Privacy protection is a serious challenge. The fundamental problem is the lack of a mechanism to help people expose appropriate amounts of their identity information when accessing pervasive computing applications. In this paper, the authors propose the Hierarchical Identity model, which enables the expression of one’s identity information ranging from precise detail to vague identity information. The authors model privacy exposure as an extensive game. By finding subgame perfect equilibria in the game, the approach achieves optimal exposure. It finds the most general identity information that a user should expose and which the service provider would accept. The authors’ experiments show that their models can reduce unnecessary identity exposure effectively.

In pervasive computing environments, personal information is expressed in digital forms to a great extent. Daily activities and personal preferences may be easily associated with personal identities. Privacy protection is a serious challenge. The fundamental problem is the lack of a mechanism to help people expose appropriate amounts of their identity information. We propose the Hierarchical Identity model. It expresses one's identity information from precise to general. We model privacy exposure as an extensive game. By finding the subgame perfect equilibria in the games, our approach achieves optimal exposure. It finds the most general identity information that a user wants to expose and a service provider accepts.

In pervasive computing environments, service discovery is an essential step for computing devices to properly discover, configure, and communicate with each other. We introduce a user-centric service discovery model, called PrudentExposure, which automates authentication processes. Traditional authentication approaches requires much users’ involvement. PrudentExposure encodes hundreds of authentication messages in a novel code word form. Moreover, we discuss how a progressive and probabilistic model can protect both users’ and service providers’ privacy. Perhaps the most serious challenge for pervasive service discovery is the integration of computing devices with people. In a challenging case, both users and service providers want the other parties to expose sensitive information first. Our model protects both users and service providers.

The involvement of only the necessary users and service providers for service discovery in pervasive computing environments is challenging. Without prudence, users' and service providers' requests or service information, their identities, and their presence information may be sacrificed. We identify that the problem may be as difficult as a chicken-and-egg problem, in which both users and service providers want the other parties to expose sensitive information first. In this paper, we propose a progressive and probabilistic approach to solve the problem. Users and service providers expose partial information in turn and avoid unnecessary exposure if there is any mismatch. Although 1 or 2 bits of information are exchanged in each message, we prove that the process converges and that the false-positive overhead decreases quickly. Experiments and hypothesis tests show that security properties hold. We implemented the approach and the performance measurements show that the approach runs efficiently on PDAs.

In pervasive computing environments, service discovery facilitates users to access network services by automating tedious manual configurations. When network services become pervasive, the number of service providers also increase dramatically. Because of security and privacy concerns, network services are segmented by service providers. Existing service discovery protocols, however, do not address how to facilitate users to properly identify and authenticate with existing service providers. Without prudence, sensitive information may be exposed. Conversely, with prudence both users and service providers prefer the other party to expose sensitive information first. We identify that even among legitimate users and service providers, there are privacy concerns that may be expressed as a chicken-and-egg problem. In this paper, we propose a progressive approach to solve the problem. Users and service providers expose minimal sensitive information in turn and identify necessary exposure during the process. Theoretical analysis, simulation, and experiments show that our approach protects sensitive information with little overhead.