The growth and presence of heterogeneous connected devices inside the home have the potential to provide increased efficiency and quality of life to the residents. Simultaneously, these devices tend to be Internet-connected and continuously monitor, collect, and transmit data about the residents and their daily lifestyle activities. Such data can be of a sensitive nature, such as camera feeds, voice commands, physiological data, and more. This data allows for the implementation of services, personalization support, and benefits offered by smart home technologies. Alas, there has been a rift of security and privacy attacks on connected home devices that compromise the security, safety, and privacy of the occupants. In this thesis, we provide a comprehensive description of the smart connected home ecosystem in terms of its assets, architecture, functionality, and capabilities. Especially, we focus on the data being collected by smart home devices. Such description and organization are necessary as a precursor to perform a rigorous security and privacy analysis of the smart home. Additionally, we seek to identify threat agents, risks, challenges, and propose some mitigation approaches suitable for home environments. Identifying these is core to characterize what is at stake, and to gain insights into what is required to build more robust, resilient, secure, and privacy-preserving smart home systems. Overall, we propose new concepts, models, and methods serving as a foundation for conducting deeper research work in particular linked to smart connected homes. In particular, we propose a taxonomy of devices; classification of data collected by smart connected homes; threat agent model for the smart connected home; and identify challenges, risks, and propose some mitigation approaches. / <p>Note: The papers are not included in the fulltext online.</p>