A study for method of construct encryption scheme of data management to Secure Data using bucket ID in Cloud Computing Environment

作者：Song You Jin; Cha Jaesang; Kang Jang Mook^*

来源：Information-An International Interdisciplinary Journal, 2012, 15(3): 1053-1064.

• Cloud
• AONT
• Fragmentation
• Privacy
• Personal Data
• Bucket ID Transformation
• Encryption

Rise in the use of cloud computing is increasing the volume of data stored and managed on a daily basis beyond TB level. Google, Naver, Daum, Yahoo and Amazon, etc. are developing proprietary distributed computing platform technologies based on massive cluster to store and manage data in large quantity. One of the best-known applications of cloud computing is u-Healthcare service. U-Healthcare adopts cloud computing to enable consolidation and sharing of medical data. Specially, Cloud computing may save system implementation costs in u-Healthcare service delivery process. Cloud computing may make sense for u-Healthcare service. However, since full trust in cloud computing service provider is a must, issues involving privacy violation or personal data disclosure may break out. Such issues occur as sensitive medical data relates to identifiable data of certain individual. To address such issues, this paper proposes AONT-based privacy protection method suited to support massive data processing in cloud environment. The method herein is suitable for processing large quantity of data, as AONT supports variation in size of fragment along with XOR operation. It can also minimize increase in DB size now appearing in relation to penetration of smartphone. So we used some exiting encryption techniques with database system to U-healthcare service. The Bucket ID Transformation is performed by modulo arithmetic or pseudo-random number generation. This method is more powerful than the previous order-preserving methods and is expected to handle data more efficiently than other methods including auxiliary B+-tree. Experiment results show that our scheme outperforms other method in encryption and query speed.

• 出版日期2012-3