Our electronic society is making fast progress for offering users greater comfort in their daily activities. Users can benefit from fast access to services; better reactivity of their physical, computing and networking environments to their own needs and habits, and preselection of information flows and relationships in which they are interested. Our digital society is eager to collect and analyze information for serving users as best as possible. Profiling users is a usual marketing activity, but new lucrative applications exploiting the huge amount of available information are emerging. The trend of Big Data has been accompanied by concerns regarding the aggregation, dissemination and re-identification of personal identifiable information. This special issue contributes to address these privacy issues, proposing privacy-enhancing technologies and solutions suited to the today's electronic society. The majority of the selected papers in this issue propose techniques and/or models for supporting privacy preferences and privacy-aware access control. The special issue also includes a contribution illustrating how the web browsing history can uniquely identify users for profiling purpose. Finally, there is a user-centered study discussing how much privacy people are willing to lose in order to gain some utilities. Collectively, these papers consider diverse contexts, ranging from social networks and web browsing, to medical/social environments and Internet of Things