TY - GEN
T1 - A data encryption scheme and GPU-based query processing algorithm for spatial data outsourcing
AU - Yoon, Min
AU - Cho, Ahra
AU - Jang, Miyoung
AU - Chang, Jae Woo
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/3/30
Y1 - 2015/3/30
N2 - With the development of cloud computing, the interest on spatial database outsourcing has been increasing. Therefore, researches for protecting location data privacy in spatial outsourced databases have been actively performed. However, FDH (Flexible Distance-Based Hashing) is easy to access original data because they do not consider data distribution. In addition, since they perform the nearest neighbor query processing by using tree-based indexes, query processing time can be increased depending on tree depth. To solve these problems, we propose a bitmap encryption scheme and a query processing algorithm for spatial database outsourcing. We propose an anchor selection algorithm using a split and merge policy based on data distribution to protect privacy of users from attackers. In addition, we reduce the communication cost for query processing by using GPU processors. Finally, we show from performance analysis that the proposed scheme shows better query processing performance than the existing scheme, while the proposed scheme guarantees users' privacy.
AB - With the development of cloud computing, the interest on spatial database outsourcing has been increasing. Therefore, researches for protecting location data privacy in spatial outsourced databases have been actively performed. However, FDH (Flexible Distance-Based Hashing) is easy to access original data because they do not consider data distribution. In addition, since they perform the nearest neighbor query processing by using tree-based indexes, query processing time can be increased depending on tree depth. To solve these problems, we propose a bitmap encryption scheme and a query processing algorithm for spatial database outsourcing. We propose an anchor selection algorithm using a split and merge policy based on data distribution to protect privacy of users from attackers. In addition, we reduce the communication cost for query processing by using GPU processors. Finally, we show from performance analysis that the proposed scheme shows better query processing performance than the existing scheme, while the proposed scheme guarantees users' privacy.
KW - cloud computing
KW - density aware
KW - GPU-based query processing algorithm
KW - grid index
KW - location data protection
KW - outsourced databases
UR - https://www.scopus.com/pages/publications/84928139254
U2 - 10.1109/35021BIGCOMP.2015.7072832
DO - 10.1109/35021BIGCOMP.2015.7072832
M3 - Conference paper
AN - SCOPUS:84928139254
T3 - 2015 International Conference on Big Data and Smart Computing, BIGCOMP 2015
SP - 202
EP - 209
BT - 2015 International Conference on Big Data and Smart Computing, BIGCOMP 2015
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2015 International Conference on Big Data and Smart Computing, BIGCOMP 2015
Y2 - 9 February 2015 through 11 February 2015
ER -