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Secure and Efficient Skyline Queries on Encrypted Data
ABSTRACT:
Outsourcing data and computation to cloud server provides a cost-effective way to
support large scale data storage and query processing. However, due to security
and privacy concerns, sensitive data (e.g., medical records) need to be protected
from the cloud server and other unauthorized users. One approach is to outsource
encrypted data to the cloud server and have the cloud server perform query
processing on the encrypted data only. It remains a challenging task to support
various queries over encrypted data in a secure and efficient way such that the
cloud server does not gain any knowledge about the data, query, and query result.
In this paper, we study the problem of secure skyline queries over encrypted data.
The skyline query is particularly important for multi-criteria decision making but
also presents significant challenges due to its complex computations. We propose a
fully secure skyline query protocol on data encrypted using semantically-secure
encryption. As a key subroutine, we present a new secure dominance protocol,
which can be also used as a building block for other queries. Furthermore, we
demonstrate two optimizations, data partitioning and lazy merging, to further
reduce the computation load. Finally, we provide both serial and parallelized
implementations and empirically study the protocols in terms of efficiency and
scalability under different parameter settings, verifying the feasibility of our
proposedsolutions.
SYSTEM REQUIREMENTS:
HARDWARE REQUIREMENTS:
 System : Pentium Dual Core.
 Hard Disk : 120 GB.
 Monitor : 15’’ LED
 Input Devices : Keyboard, Mouse
 Ram : 1 GB
SOFTWARE REQUIREMENTS:
 Operating system : Windows 7.
 Coding Language : JAVA.
 Tool : Netbeans 7.2.1
 Database : MYSQL
REFERENCE:
Jinfei Liu, member, IEEE, Juncheng Yang, member, IEEE, Li Xiong, member,
IEEE, and Jian Pei, Fellow, IEEE, “Secure and Efficient Skyline Queries on
Encrypted Data”, IEEE Transactions on Knowledge and Data Engineering,
Volume: 31 , Issue: 7 , July 1 2019.

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Secure and efficient skyline queries on encrypted data

  • 1. Secure and Efficient Skyline Queries on Encrypted Data ABSTRACT: Outsourcing data and computation to cloud server provides a cost-effective way to support large scale data storage and query processing. However, due to security and privacy concerns, sensitive data (e.g., medical records) need to be protected from the cloud server and other unauthorized users. One approach is to outsource encrypted data to the cloud server and have the cloud server perform query processing on the encrypted data only. It remains a challenging task to support various queries over encrypted data in a secure and efficient way such that the cloud server does not gain any knowledge about the data, query, and query result. In this paper, we study the problem of secure skyline queries over encrypted data. The skyline query is particularly important for multi-criteria decision making but also presents significant challenges due to its complex computations. We propose a fully secure skyline query protocol on data encrypted using semantically-secure encryption. As a key subroutine, we present a new secure dominance protocol, which can be also used as a building block for other queries. Furthermore, we demonstrate two optimizations, data partitioning and lazy merging, to further reduce the computation load. Finally, we provide both serial and parallelized implementations and empirically study the protocols in terms of efficiency and scalability under different parameter settings, verifying the feasibility of our proposedsolutions. SYSTEM REQUIREMENTS: HARDWARE REQUIREMENTS:
  • 2.  System : Pentium Dual Core.  Hard Disk : 120 GB.  Monitor : 15’’ LED  Input Devices : Keyboard, Mouse  Ram : 1 GB SOFTWARE REQUIREMENTS:  Operating system : Windows 7.  Coding Language : JAVA.  Tool : Netbeans 7.2.1  Database : MYSQL REFERENCE: Jinfei Liu, member, IEEE, Juncheng Yang, member, IEEE, Li Xiong, member, IEEE, and Jian Pei, Fellow, IEEE, “Secure and Efficient Skyline Queries on Encrypted Data”, IEEE Transactions on Knowledge and Data Engineering, Volume: 31 , Issue: 7 , July 1 2019.