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In this paper, we consider a scenario where a user queries a user profile database, maintained by a social networking service provider, to find out some users whose profiles are similar to the profile specified by the querying user. A typical example of this application is online dating. Most recently, an online data site, Ashley Madison, was hacked, which results in disclosure of a large number of...
In a two-server password-authenticated key exchange (PAKE) protocol, a client splits its password and stores two shares of its password in the two servers, respectively, and the two servers then cooperate to authenticate the client without knowing the password of the client. In case one server is compromised by an adversary, the password of the client is required to remain secure. In this paper, we...
Many techniques for privacy-preserving data mining (PPDM) have been investigated over the past decade. Such techniques, however, usually incur heavy computational and communication cost on the participating parties and thus entities with limited resources may have to refrain from participating in the PPDM process. To address this issue, one promising solution is to outsource the tasks to the cloud...
Outsourcing data and computation to the cloud is increasingly common. However, the data to be outsourced is often privacy-sensitive (e.g., geospatial data, social network data, and Internet network traffic data) and thus it is typically outsourced after being properly encrypted. Graph is one of the most common ways to model and represent the data in many applications, including geospatial data in...
Private record linkage protocols allow multiple parties to exchange matching records, which refer to the same entities or have similar values, while keeping the non-matching ones secret. Conventional protocols are based on computationally expensive cryptographic primitives and therefore do not scale. To address these scalability issues, hybrid protocols have been recently proposed that combine differential...
Extracting useful knowledge from social network datasets is a challenging problem. To add to the difficulty of this problem, privacy concerns that exist for many social network datasets have restricted the ability to analyze these networks and consequently to maximize the knowledge that can be extracted from them. This paper addresses this issue by introducing the problem of data trustworthiness in...
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