The challenge of preserving a user’s location privacy is more important now than ever before with the proliferation of handheld devices and the pervasive use of location based services. To protect location privacy, we must ensure k-anonymity so that the user remains indistinguishable among k-1 other users. There is no better way but to use a location anonymizer (LA) to achieve k-anonymity. Howe...

Employing a two-by-two factorial design that manipulates whether dictator groups are single or mixed-sex and whether procedures are single or double-blind, we examine gender effects in a standard dictator game. No gender effects were found in any of the experimental treatments for the mean or median levels of giving, or for the propensity to give nothing. However, females chose to give away hal...

In 2001, two information theoretic anonymity metrics were proposed: the effective anonymity set size and the degree of anonymity. Here, we propose an abstract model for a general anonymity system which is consistent with the definition of anonymity on which the metrics are based. We revisit entropybased anonymity metrics, and we apply them to Crowds, a practical anonymity system. We discuss the...

Protection of users’ privacy has been a central issue for location-based services (LBSs). In this paper, we classify two kinds of privacy protection requirements in LBS: location anonymity and identifier anonymity. While the location cloaking technique under the k-anonymity model can provide a good protection of users’ privacy, it reduces the resolution of location information and, hence, may d...

Microaggregation is a family of methods for statistical disclosure control (SDC) of microdata (records on individuals and/or companies), that is, for masking microdata so that they can be released without disclosing private information on the underlying individuals. Microaggregation techniques are currently being used by many statistical agencies. The principle of microaggregation is to group o...

Data aggregation is a central principle underlying many applications in computer science, from artificial intelligence to data security and privacy. Microaggregation is a special clustering problem where the goal is to cluster a set of points into groups of at least k points in such a way that groups are as homogeneous as possible. A usual homogeneity criterion is the minimization of the within...

In today’s globally networked society, there is a dual demand on both information sharing and information protection. A typical scenario is that two parties wish to integrate their private databases to achieve a common goal beneficial to both, provided that their privacy requirements are satisfied. In this paper, we consider the goal of building a classifier over the integrated data while satis...

The preservation of privacy when publishing spatiotemporal traces of mobile humans is a field that is receiving growing attention. However, while more and more services offer personalized privacy options to their users, few trajectory anonymization algorithms are able to handle personalization effectively, without incurring unnecessary information distortion. In this paper, we study the problem...

Dynamic and smart Internet of Things (IoT) infrastructures allow the development healthcare systems, which are equipped with mobile health embedded sensors to enable a broad range applications. These IoT applications provide access clients’ information. However, rapid increase in number devices social networks has generated concerns regarding secure sharing client’s location. In this regard, fe...