TY - GEN
T1 - Efficient parallel summation on encrypted database system
AU - Horio, Kentaro
AU - Kawashima, Hideyuki
AU - Tatebe, Osamu
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/3/17
Y1 - 2017/3/17
N2 - The spread of cloud computing services has resulted in data storage and data management services being outsourced to servers operated by a third party. This outsourcing can raise some security concerns because the administrators of the servers may snoop and explore the data. Encrypted database systems provide a certain level of security by encrypting the data they contain. It provides relational operators over encrypted data, which does not require data decryption and blocks the incidents. The disadvantage of this scheme is the considerable execution expense associated with data processing. Current encrypted database systems do not provide sufficient performance improvement. We focus on the summation operator in this paper, and we propose a parallel execution scheme of sum aggregation over the encrypted database. The proposed method employs task parallelism, and we assign a fine-grained data objects for each thread. We evaluate the proposed method on our prototype database system implemented in C++ and OpenMP. The result showed that proposed method achieves 15.99× performance improvement compared with a conventional method.
AB - The spread of cloud computing services has resulted in data storage and data management services being outsourced to servers operated by a third party. This outsourcing can raise some security concerns because the administrators of the servers may snoop and explore the data. Encrypted database systems provide a certain level of security by encrypting the data they contain. It provides relational operators over encrypted data, which does not require data decryption and blocks the incidents. The disadvantage of this scheme is the considerable execution expense associated with data processing. Current encrypted database systems do not provide sufficient performance improvement. We focus on the summation operator in this paper, and we propose a parallel execution scheme of sum aggregation over the encrypted database. The proposed method employs task parallelism, and we assign a fine-grained data objects for each thread. We evaluate the proposed method on our prototype database system implemented in C++ and OpenMP. The result showed that proposed method achieves 15.99× performance improvement compared with a conventional method.
KW - Data Security
KW - Database Systems
KW - Encryption
KW - Query Processing
UR - http://www.scopus.com/inward/record.url?scp=85017630608&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85017630608&partnerID=8YFLogxK
U2 - 10.1109/BIGCOMP.2017.7881735
DO - 10.1109/BIGCOMP.2017.7881735
M3 - Conference contribution
AN - SCOPUS:85017630608
T3 - 2017 IEEE International Conference on Big Data and Smart Computing, BigComp 2017
SP - 178
EP - 185
BT - 2017 IEEE International Conference on Big Data and Smart Computing, BigComp 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2017 IEEE International Conference on Big Data and Smart Computing, BigComp 2017
Y2 - 13 February 2017 through 16 February 2017
ER -