TY - GEN
T1 - Ensuring query completeness in outsourced database using order-preserving encryption
AU - Shen, Ning
AU - Yeh, Jyh Haw
AU - Chen, Chien Ming
AU - Chen, Yeh Cheng
AU - Zhang, Yunpeng
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/12
Y1 - 2019/12
N2 - Nowadays database outsourcing has become business owners' preferred option and they are benefiting from its flexibility, reliability, and low cost. However, because database service providers cannot always be fully trusted and data owners will no longer have a direct control over their own data, how to make the outsourced data secure becomes a hot research topic. From the data integrity protection aspect, the client wants to make sure the data returned is correct, complete, and up-to-date. Previous research work in literature put more efforts on data correctness, while data completeness is still a challenging problem to solve. There are some existing works that tried to protect the completeness of data. Unfortunately, these solutions were considered not fully solving the problem because of their high communication or computation overhead. The implementations and limitations of existing works will be further discussed in this paper. From the data confidentiality protection aspect, order-preserving encryption (OPE) is a widely used encryption scheme in protecting data confidentiality. It allows the client to perform range queries and some other operations such as GROUP BY and ORDER BY over the OPE encrypted data. Therefore, it is worthy to develop a solution that allows user to verify the query completeness for an OPE encrypted database so that both data confidentiality and completeness are both protected. Inspired by this motivation, we propose a new data completeness protecting scheme by inserting fake tuples into databases. Both the real and fake tuples are OPE encrypted and thus the cloud server cannot distinguish among them. While our new scheme is much more efficient than all existing approaches, the level of security protection remains the same.
AB - Nowadays database outsourcing has become business owners' preferred option and they are benefiting from its flexibility, reliability, and low cost. However, because database service providers cannot always be fully trusted and data owners will no longer have a direct control over their own data, how to make the outsourced data secure becomes a hot research topic. From the data integrity protection aspect, the client wants to make sure the data returned is correct, complete, and up-to-date. Previous research work in literature put more efforts on data correctness, while data completeness is still a challenging problem to solve. There are some existing works that tried to protect the completeness of data. Unfortunately, these solutions were considered not fully solving the problem because of their high communication or computation overhead. The implementations and limitations of existing works will be further discussed in this paper. From the data confidentiality protection aspect, order-preserving encryption (OPE) is a widely used encryption scheme in protecting data confidentiality. It allows the client to perform range queries and some other operations such as GROUP BY and ORDER BY over the OPE encrypted data. Therefore, it is worthy to develop a solution that allows user to verify the query completeness for an OPE encrypted database so that both data confidentiality and completeness are both protected. Inspired by this motivation, we propose a new data completeness protecting scheme by inserting fake tuples into databases. Both the real and fake tuples are OPE encrypted and thus the cloud server cannot distinguish among them. While our new scheme is much more efficient than all existing approaches, the level of security protection remains the same.
KW - Database outsourcing
KW - Order-preserving encryption
KW - Query completeness
UR - http://www.scopus.com/inward/record.url?scp=85085523486&partnerID=8YFLogxK
U2 - 10.1109/ISPA-BDCloud-SustainCom-SocialCom48970.2019.00116
DO - 10.1109/ISPA-BDCloud-SustainCom-SocialCom48970.2019.00116
M3 - Conference contribution
AN - SCOPUS:85085523486
T3 - Proceedings - 2019 IEEE Intl Conf on Parallel and Distributed Processing with Applications, Big Data and Cloud Computing, Sustainable Computing and Communications, Social Computing and Networking, ISPA/BDCloud/SustainCom/SocialCom 2019
SP - 776
EP - 783
BT - Proceedings - 2019 IEEE Intl Conf on Parallel and Distributed Processing with Applications, Big Data and Cloud Computing, Sustainable Computing and Communications, Social Computing and Networking, ISPA/BDCloud/SustainCom/SocialCom 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 17th IEEE International Conference on Parallel and Distributed Processing with Applications, 9th IEEE International Conference on Big Data and Cloud Computing, 9th IEEE International Conference on Sustainable Computing and Communications, 12th IEEE International Conference on Social Computing and Networking, ISPA/BDCloud/SustainCom/SocialCom 2019
Y2 - 16 December 2019 through 18 December 2019
ER -