Efficient Technique for Privacy Preserving Publishing of Set Valued Data on Cloud

G. Elavarasan and Dr.S. Veni


Cloud computing is an emerging technology to store, handle and access the huge volume of data from anywhere and in anytime. The data in the cloud also contain private information and sensitive information. The concerns of privacy breaches have hindered the development of cloud computing. A data partitioning technique called as extended quasi identifier partitioning (EQI-partitioning)was proposed for privacy preserving in cloud computing. The EQI partitioning technique disassociates the data records which participate in identifying combinations. This technique guaranteed the privacy to cloud data. But this technique protects only the data privacy and it does not considered the information loss and security of cloud data. In this paper, the information loss is considered by using l-diversity and 𝑘𝑘𝑚𝑚 anonymity in EQI partitioning scheme. In addition to that, a multi level accessibility model is developed to provide the security based on the user's level. The sensitivity value of data stored in cloud computing is computed from the availability, integrity and confidentiality of data. Then identity based proxy re-encryption scheme is used to provide the security for different level of users. Thus the proposed work reduces the information loss and provides the security to data in the cloud. The experimental results are conduced to prove the effectiveness of the proposed work in terms of average relative error, time, anonymization time and information loss

Issue: 05-Special Issue

Year: 2017

Pages: 120-128

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