In this paper we describe our approach on protecting user privacy in smart environments, particularly smart homes, which we call eHomes. These are environments with devices such as sensors, computational units, actors, which are seamlessly integrated in the environment, and objects we use in our everyday life. In order to provide more convenience to its users such environments can be personalized.As these environments become ubiquitous, thus supporting mobility of the users, new privacy threats arise. These are based on the digital traces and personal information which is left while visiting different environments. We provide a practical approach to minimize these traces and information disclosure by applying negotiation, identity management, and anonymous credentials. Also, we discuss the protection of eHomes from malicious users.

No abstract

New developments and decreasing costs of electronic appliances enable the realization of pervasive systems in our daily environment. In our work, we focus on eHome systems. The cost-intensive repetitive development process for every new eHome environment is one of the major problems preventing their widespread use. So, we transformed the repetitive development process to a single one, followed by a repetitive configuration process. To support this configuration process, we introduce a model capable of storing all the parameters relevant for this specific process. To enable semiautomatic configuration based on the model, a specification is required beforehand. In this paper, we will show how the necessary specification is covered by the introduced model, and how the model supports the eHome system configuration and context inferring at runtime.

In future smart homes functionality will be provided to the inhabitants by software services decoupled from the underlying hardware devices. While this will enhance flexibility and will allow to provide cross-functionalities across multiple devices it will also lead to resource conflicts. Future devices will provide basic functionalities which are used by separate higher level services. Each person will use a number of different services and each environment can be inhabited by multiple users at the same time. All respective services have to be executed based on a limited number of devices, which will result in resource conflicts. In this paper we describe how we extended our existing dependency management approach for smart home services with a mechanism for monitoring service bindings and handling access control based on priority groups.

No abstract