TY - GEN
T1 - ImageProof
T2 - 35th IEEE International Conference on Data Engineering, ICDE 2019
AU - Guo, Shangwei
AU - XU, Jianliang
AU - Zhang, Ce
AU - Xu, Cheng
AU - Xiang, Tao
N1 - Funding Information:
The authors are grateful to the anonymous reviewers for their valuable comments and suggestions that improved the quality of this paper. This work was supported by grants from the HK-RGC under Project Nos. 12201018, 12244916, and C1008-16G. Tao Xiang was supported by the National Natural Science Foundation of China under grant No. 61672118.
PY - 2019/4
Y1 - 2019/4
N2 - With the explosive growth of online images and the popularity of search engines, a great demand has arisen for small and medium-sized enterprises to build and outsource large-scale image retrieval systems to cloud platforms. While reducing storage and retrieval burdens, enterprises are at risk of facing untrusted cloud service providers. In this paper, we take the first step in studying the problem of query authentication for large-scale image retrieval. Due to the large size of image files, the main challenges are to (i) design efficient authenticated data structures (ADSs) and (ii) balance search, communication, and verification complexities. To address these challenges, we propose two novel ADSs, the Merkle randomized k-d tree and the Merkle inverted index with cuckoo filters, to ensure the integrity of query results in each step of image retrieval. For each ADS, we develop corresponding search and verification algorithms on the basis of a series of systemic design strategies. Furthermore, we put together the ADSs and algorithms to design the final authentication scheme for image retrieval, which we name ImageProof. We also propose several optimization techniques to improve the performance of the proposed ImageProof scheme. Security analysis and extensive experiments are performed to show the robustness and efficiency of ImageProof.
AB - With the explosive growth of online images and the popularity of search engines, a great demand has arisen for small and medium-sized enterprises to build and outsource large-scale image retrieval systems to cloud platforms. While reducing storage and retrieval burdens, enterprises are at risk of facing untrusted cloud service providers. In this paper, we take the first step in studying the problem of query authentication for large-scale image retrieval. Due to the large size of image files, the main challenges are to (i) design efficient authenticated data structures (ADSs) and (ii) balance search, communication, and verification complexities. To address these challenges, we propose two novel ADSs, the Merkle randomized k-d tree and the Merkle inverted index with cuckoo filters, to ensure the integrity of query results in each step of image retrieval. For each ADS, we develop corresponding search and verification algorithms on the basis of a series of systemic design strategies. Furthermore, we put together the ADSs and algorithms to design the final authentication scheme for image retrieval, which we name ImageProof. We also propose several optimization techniques to improve the performance of the proposed ImageProof scheme. Security analysis and extensive experiments are performed to show the robustness and efficiency of ImageProof.
KW - Bag of visual word
KW - Content based image retrieval
KW - Query authentication
KW - Verifiable
UR - http://www.scopus.com/inward/record.url?scp=85068015808&partnerID=8YFLogxK
U2 - 10.1109/ICDE.2019.00099
DO - 10.1109/ICDE.2019.00099
M3 - Conference proceeding
AN - SCOPUS:85068015808
T3 - Proceedings - International Conference on Data Engineering
SP - 1070
EP - 1081
BT - Proceedings - 2019 IEEE 35th International Conference on Data Engineering, ICDE 2019
PB - IEEE Computer Society
Y2 - 8 April 2019 through 11 April 2019
ER -