PROJECT TITLE :

Privacy-Preserving Multi-Keyword Ranked Search over Encrypted Cloud Data - 2014

ABSTRACT:

With the advent of Cloud Computing, data owners are motivated to outsource their complex data management systems from local sites to the commercial public cloud for great flexibility and economic savings. But for protecting data privacy, sensitive data have to be encrypted before outsourcing, which obsoletes traditional data utilization based on plaintext keyword search. Thus, enabling an encrypted cloud data search service is of paramount importance. Considering the large number of data users and documents in the cloud, it is necessary to allow multiple keywords in the search request and return documents in the order of their relevance to these keywords. Related works on searchable encryption focus on single keyword search or Boolean keyword search, and rarely sort the search results. In this paper, for the first time, we define and solve the challenging problem of privacy-preserving multi-keyword ranked search over encrypted data in Cloud Computing (MRSE). We establish a set of strict privacy requirements for such a secure cloud data utilization system. Among various multi-keyword semantics, we choose the efficient similarity measure of "coordinate matching," i.e., as many matches as possible, to capture the relevance of data documents to the search query. We further use "inner product similarity" to quantitatively evaluate such similarity measure. We first propose a basic idea for the MRSE based on secure inner product computation, and then give two significantly improved MRSE schemes to achieve various stringent privacy requirements in two different threat models. To improve search experience of the data search service, we further extend these two schemes to support more search semantics. Thorough analysis investigating privacy and efficiency guarantees of proposed schemes is given. Experiments on the real-world data set further show proposed schemes indeed introduce low overhead on computation and Communication.


Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here


PROJECT TITLE : Towards Personalized Privacy-Preserving Incentive for Truth Discovery in Mobile Crowdsensing Systems ABSTRACT: It is essential to have incentive mechanisms in place in mobile crowdsensing (MCS) systems in order
PROJECT TITLE : TPPR: A Trust-Based and Privacy-Preserving Platoon Recommendation Scheme in VANET ABSTRACT: A novel vehicle driving paradigm known as the vehicle platoon, which organizes a group of vehicles in the nose-to-tail
PROJECT TITLE : Privacy-Preserving Diverse Keyword Search and Online Pre-Diagnosis in Cloud Computing ABSTRACT: With the development of the Mobile Healthcare Monitoring Network (MHMN), patients' data collected by body sensors
PROJECT TITLE : Multi-Access Filtering for Privacy-Preserving Fog Computing ABSTRACT: The military and other traditionally conservative and sensitive sectors, such as government and law enforcement, are beginning to show an increased
PROJECT TITLE : A Conditional Privacy-Preserving Certificateless Aggregate Signature Scheme in the Standard Model for VANETs ABSTRACT: Vehicular ad hoc networks, also known as VANETs, are the communication foundation for future

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry