Improving Database Storage Usability with the Cloud-Based Architecture

Database is widely used for information storage and management. With the explosion of the data size, the requirement of the storage capacity is growing dramatically. Cloud offers clients a scalable solution to meet the demand of the increasing space. A cloud service, if used and managed properly, can increase the resource usability and provide more secure services. In this paper, we propose a cloud-based database architecture that increases the database storage usability meanwhile ensuring the data security. In this architecture, we move the database storage into a shared cloud-based server and leave the database engine at user’s domain. The transmission of database physical files between the cloud and the database engine is achieved through Network File System. To avoid information leakage incurred by attacks on the cloud, the physical files stored in the cloud were encrypted by the database engine. To verify our idea, we used MySQL as our study case and evaluated the performance of this new architecture. A series of experiments indicate that the proposed architecture is promising in improving storage sharing, meanwhile guaranteeing the data security.

[1]  PukdesreeSorapak,et al.  Performance evaluation of distributed database on PC cluster computers , 2011 .

[2]  Ken Eguro,et al.  Transaction processing on confidential data using cipherbase , 2015, 2015 IEEE 31st International Conference on Data Engineering.

[3]  Radu Sion,et al.  TrustedDB: A Trusted Hardware-Based Database with Privacy and Data Confidentiality , 2011, IEEE Transactions on Knowledge and Data Engineering.

[4]  Sorapak Pukdesree,et al.  Performance evaluation of distributed database on PC cluster computers , 2011 .

[5]  Shaolei Ren,et al.  Toward integrity assurance of outsourced computing - a game theoretic perspective , 2016, Future Gener. Comput. Syst..

[6]  Srinivas Devadas,et al.  Intel SGX Explained , 2016, IACR Cryptol. ePrint Arch..

[7]  Christos Gkantsidis,et al.  VC3: Trustworthy Data Analytics in the Cloud Using SGX , 2015, 2015 IEEE Symposium on Security and Privacy.

[8]  Abel N. Kho,et al.  SMCQL: Secure Query Processing for Private Data Networks , 2016, Proc. VLDB Endow..

[9]  Jinpeng Wei,et al.  Toward protecting control flow confidentiality in cloud-based computation , 2015, Comput. Secur..

[10]  Xiaohong Jiang,et al.  MtMR: Ensuring MapReduce Computation Integrity with Merkle Tree-Based Verifications , 2018, IEEE Transactions on Big Data.

[11]  Md. Saiful Azad,et al.  MySQL performance analysis on a limited resource server: Fedora vs. Ubuntu Linux , 2010, SpringSim.

[12]  Mudhakar Srivatsa,et al.  Result Integrity Check for MapReduce Computation on Hybrid Clouds , 2013, 2013 IEEE Sixth International Conference on Cloud Computing.

[13]  Rishabh Poddar,et al.  Arx: A Strongly Encrypted Database System , 2016, IACR Cryptol. ePrint Arch..

[14]  Siu-Ming Yiu,et al.  Secure query processing with data interoperability in a cloud database environment , 2014, SIGMOD Conference.