In the post-genomic era, large-scale personal DNA sequences are produced and collected for genetic medical diagnoses and new drug discovery, which, however, simultaneously poses serious challenges to the protection of personal genomic privacy. Existing genomic privacy-protection methods are either time-consuming or with low accuracy. To tackle these problems, this paper proposes a sequence simi...

Like many peer-to-peer applications, anonymous communication systems are vulnerable to freeriders, peers that use the system while providing little or no service to others. To complicate matters, the identity of the free-rider is obscured by the very anonymity such systems are designed to provide, imposing challenging design constraints for incentive mechanisms to discourage free-riding. We arg...

Publishing data for analysis from a micro data table containing sensitive attributes, while maintaining individual privacy, is a problem of increasing significance today. The k-anonymity model was proposed for privacy preserving data publication. While focusing on identity disclosure, k-anonymity model fails to protect attribute disclosure to some extent. Many efforts are made to enhance the k-...

The problem of the release of anonymized microdata is an important topic in the fields of statistical disclosure control (SDC) and privacy preserving data publishing (PPDP), and yet it remains sufficiently unsolved. In these research fields, k-anonymity has been widely studied as an anonymity notion for mainly deterministic anonymization algorithms, and some probabilistic relaxations have been ...

Privacy protection for incremental data has a great effect on data availability and practicality. Kanonymity is an important approach to protect data privacy in data publishing scenario. However, it is a NP-hard problem for optimal k-anonymity on dataset with multiple attributes. Most partitions in k-anonymity at present are single-dimensional. Now research on k-anonymity mainly focuses on gett...

By reducing inhibition, enhancing participation, and by increasing the number of ideas generated, anonymity is expected to improve communication and decision making and to enhance group performance. However, empirical evidence is inconclusive and provides a rather confusing understanding of the real effects of anonymity in group support systems (GSS). This paper addresses the state of empirical...

This research meta-analyzed 13 journal articles regarding anonymity and conformity to group norms. Results showed that there was a positive relationship between anonymity and conformity, with a weighted mean effect size = 0.16, which was in line with the social identity model of deindividuation effects. This study also investigated the differences between different types of anonymity and found ...

Users of location-based services (LBSs) may have serious privacy concerns when using these technologies since their location can be utilized by adversaries to infer privacy-sensitive information about them. In this work, we analyze the mainstream anonymity solutions proposed for LBSs based on k-anonymity, and point out that these do not follow the safe assumptions as per the original definition...

In this paper we look closely at the popular metric of anonymity, the anonymity set, and point out a number of problems associated with it. We then propose an alternative information theoretic measure of anonymity which takes into account the probabilities of users sending and receiving the messages and show how to calculate it for a message in a standard mix-based anonymity system. We also use...

While information systems provide modern society with great convenience, it also poses new problems in maintaining social order. One of its negative influences is the anonymity of cyberspace, which makes identity tracing a noteworthy predicament which poses obstacles in detection and investigations. It has been found that cyber anonymity has critical impacts on criminal motivation, and the phen...