  Data markets serve as crucial platforms facilitating data discovery,
exchange, sharing, and integration among data users and providers. However, the
paramount concern of privacy has predominantly centered on protecting privacy
of data owners and third parties, neglecting the challenges associated with
protecting the privacy of data buyers. In this article, we address this gap by
modeling the intricacies of data buyer privacy protection and investigating the
delicate balance between privacy and purchase cost. Through comprehensive
experimentation, our results yield valuable insights, shedding light on the
efficacy and efficiency of our proposed approaches.
