The concept of Smart Home where appliances, sensors, actuators, displays and computing resources are connected and interact to support the life of the citizen is being increasingly researched. In this context, the Wi-Fi communication technology has grown to become the de-facto standard for data communications in Smart Home environments, with cordless telephony being dominated by the DECT protocol. Even though both technologies incorporate sets of security features aimed at securing the confidentiality and integrity of the communications, the nature and the design of both radio-frequency protocols make them vulnerable, up to a certain extent, to privacy leakages through traffic analysis attacks. In this paper we explore the information leakage vulnerabilities inherent to these technologies and their potential impact on citizens’ privacy in the context of the Smart Home. We demonstrate how the websites visited by a smart device can be inferred by applying machine learning and pattern matching techniques to eavesdropped encrypted traffic. ; JRC.G.6-Digital Citizen Security