TY - GEN
T1 - Secure, Available, Verifiable, and Efficient Range Query Processing on Outsourced Datasets
AU - Li, Meng
AU - Gao, Jianbo
AU - Zhang, Zijian
AU - Conti, Mauro
AU - Alazab, Mamoun
PY - 2024/8/20
Y1 - 2024/8/20
N2 - Range queries allow data users to outsource their data to a Cloud Server (CS) that responds to data users who submit a request with range conditions. However, security concerns hinder the wide-scale adoption. Existing works neglect item availability, fail to protect secure verification or sacrifice search accuracy for efficiency. In this paper, we propose Secure, Available, Verifiable, and Efficient (SAVE) range query processing, which has three distinctive features. (1) Secure availability checking against a malicious CS: we design a keyed index-based secure verification mechanism to check the availability of matched nodes, including validity and freshness. (2) Secure result verification: we design a targeted verification mechanism for result correctness and completeness while not compromising security. (3) Improved efficiency and accuracy: we design a lay-ered encoding method to improve search efficiency and accuracy. We formally stated and proved the security of SAVE in the random oracle model. We conducted extensive experiments over the Yelp and FourSquare dataset to validate the efficiency, e.g., a query over 10 thousand data items only needs 19.4 ms to get queried results and 3.5 ms for local verification.
AB - Range queries allow data users to outsource their data to a Cloud Server (CS) that responds to data users who submit a request with range conditions. However, security concerns hinder the wide-scale adoption. Existing works neglect item availability, fail to protect secure verification or sacrifice search accuracy for efficiency. In this paper, we propose Secure, Available, Verifiable, and Efficient (SAVE) range query processing, which has three distinctive features. (1) Secure availability checking against a malicious CS: we design a keyed index-based secure verification mechanism to check the availability of matched nodes, including validity and freshness. (2) Secure result verification: we design a targeted verification mechanism for result correctness and completeness while not compromising security. (3) Improved efficiency and accuracy: we design a lay-ered encoding method to improve search efficiency and accuracy. We formally stated and proved the security of SAVE in the random oracle model. We conducted extensive experiments over the Yelp and FourSquare dataset to validate the efficiency, e.g., a query over 10 thousand data items only needs 19.4 ms to get queried results and 3.5 ms for local verification.
UR - http://www.scopus.com/inward/record.url?scp=85202898921&partnerID=8YFLogxK
U2 - 10.1109/ICC51166.2024.10622526
DO - 10.1109/ICC51166.2024.10622526
M3 - Conference Paper published in Proceedings
AN - SCOPUS:85202898921
SN - 9781728190556
T3 - IEEE International Conference on Communications
SP - 1376
EP - 1381
BT - ICC 2024 - IEEE International Conference on Communications
A2 - Valenti, Matthew
A2 - Reed, David
A2 - Torres, Melissa
PB - IEEE, Institute of Electrical and Electronics Engineers
CY - United States
T2 - 59th Annual IEEE International Conference on Communications, ICC 2024
Y2 - 9 June 2024 through 13 June 2024
ER -