Attribute-Hiding Public Key Encryption Construction Based On Secure Multi-Party Computing

With the sustainable development of the Internet,the amount of data on the network is also increasing dramatically.Since the data contain sensitive commercial secrets,military information and personal privacy,this makes people pay much attention to preserving the private information when processing data.Therefore,as a prominent issue,data privacy protection has been addressed under this situation,which can be divided into privacypreserving cooperative computation and privacy-preserving data transmission.Privacy-preserving cooperative computation involves how to calculate a common function on the premise of protecting individual private data of multiple parties and privacy-preserving data transmission refers to how to ensure that data cannot be eavesdropped by outside and inside adversaries during data transmission.Data transmission and data computation are two important issues in data processing.Thus this paper first studies privacy-preserving cooperative computation,and further studies the privacy-preserving data transmission based some techniques of privacy-preserving cooperative computation.For the privacy-preserving cooperation computation,we study an open problem within secure multi-party computation:privacy-preserving polynomial interpolation.This problem is a basic issue in secure multi-party computation.It can be often used as a basic tool to solve privacy-preserving predicative analysis.In order to cope with this issue,we first transform privacy-preserving polynomial interpolation to the calculation on privacy-preserving function values,and then propose a secure scalar product protocol.Finally,we use the secure scalar product protocol to solve the privacy-preserving polynomial interpolation and further give some applicable examples on privacy-preserving predicative analysis.Our main contributions:it is first time to present a solution on the open issue,privacy-preserving polynomial interpolation,within secure multi-party computation.We then offer two application examples of our protocol on privacy-preserving predictive analysis:privacy-preserving disease diagnosis and privacy-preserving investment prediction,which has a great practical significance.For the privacy-preserving data transmission,this paper studies attribute-hiding fuzzy encryption.This encryption can not only preserve data privacy,but also preserve attribute privacy during data transmission,which has stronger capability of privacy protection.Therefore,it has important research significance.In this thesis,we propose a new attribute-hiding fuzzy encryption scheme based on the overlap distance.In order to design this scheme,we develop a new encoding to embedding fuzzy facility,and transform the original problem into inner product encryption with fuzzy property.Meanwhile,we use a fast decryption to improve efficiency.Finally,we present some practical application examples of the scheme.Our main contributions is that an attribute hiding fuzzy public key encryption scheme is proposed,which extends the number field from binary to decimal and meanwhile is able to locate accurate decryption key quickly to highlight higher efficiency.The scheme is applied to fuzzy searchable encryption and the attribute-hiding closet substring encryption,which shows that this scheme has wide application.