Privacy-preserving electronic bartering

E-commerce applications like online shopping, e-marketplaces, and e-banking are becoming more and more prevalent in our daily lives. While providing a lot of convenience, these applications generally require the disclosing of sensitive personal data. Typically, it is not transparent for their users what the personal data are used for. A majority of users may be willing to share sensitive personal data on the Internet to some extent when there is a balance between the involved benefits and drawbacks. However, this is certainly not the case if those data (e.g., one's room for negotiation) have the potential to adversely affect e-commerce transactions which, in particular, may occur particularly in the context of online bartering marketplaces. The research goal of this thesis is to advance the privacy-protection of online bartering marketplaces such that users do not have to disclose private data (including their offers/demands as well as the quantities thereof) to anyone in order to find suitable trade partners. Our approach is to design privacy-preserving protocols that can be used as a key component of a bartering system allowing its users to barter their commodities in a privacy-preserving fashion. More precisely, we devise a novel privacy-preserving bartering protocol for the two-party case providing security against active adversaries as well as two novel privacy-preserving bartering protocols for the multi-party case which provide security against passive and active adversaries, respectively. The focus of this thesis is on the much more complicated multi-party case which, compared to the two-party case, requires fundamentally different design approaches as well as the development of novel privacy-preserving building blocks for comparison and selection operations that are of general interest beyond the context of bartering. Using our privacy-preserving multi-party bartering protocols (which are shown to be practical for a limited number of parties) as a key component, we model a bartering system that allows an arbitrary number of parties (arriving at the system over time) to barter their commodities in a privacy-preserving fashion. The implementation and the simulation of our novel privacy-preserving bartering model as well as the comparison to the most prominent conventional bartering models show that the modeled privacy-preserving bartering system is practical