Location-based applications refer to those that use location data in a prominent manner. Location data can be very effective for service provisioning, enabling the birth of a new generation of information services. Although data security and privacy issues have been extensively investigated in several domains, current techniques are not readily applicable to location-based applications. Conciliating the effectiveness of these applications with privacy concerns constitutes a unique challenge, mostly due to the semantic richness of location and time information. Research in this field involves aspects of spatio-temporal reasoning, query processing, system security, statistical inference, and more importantly, anonymization techniques. Several research groups have been working in recent years to identify privacy attacks and defense techniques in this domain.

This state-of-the-art survey provides a solid ground for researchers approaching this topic to understand current achievements through a common categorization of privacy threats and defense techniques. This objective is particularly challenging considering the specific (and often implicit) assumptions that characterize the recent literature on privacy in location-based services.

The book also illustrates the many facets that make the study of this topic a particularly interesting research subject, including topics that go beyond privacy preserving transformations of service requests, and include access control, privacy preserving publishing of moving object data, privacy in the use of specific positioning technology, and privacy in vehicular network applications.

This two volume set LNCS 9642 and LNCS 9643 constitutes the refereed proceedings of the 21st International Conference on Database Systems for Advanced Applications, DASFAA 2016, held in Dallas, TX, USA, in April 2016. The 61 full papers presented were carefully reviewed and selected from a total of 183 submissions. The papers cover the following topics: crowdsourcing, data quality, entity identification, data mining and machine learning, recommendation, semantics computing and knowledge base, textual data, social networks, complex queries, similarity computing, graph databases, and miscellaneous, advanced applications.