Computer Science

Computer Science ›› 2023, Vol. 50 ›› Issue (9): 26-34.doi: 10.11896/jsjkx.230400033

• Data Security • Previous Articles     Next Articles

Efficient Encrypted Image Content Retrieval System Based on SecureCNN

LU Yuhan, CHEN Liquan, WANG Yu, HU Zhiyuan   

  1. School of Cyberspace Security,Southeast University,Nanjing 210000,China
  • Received:2023-04-05 Revised:2023-07-07 Online:2023-09-15 Published:2023-09-01
  • About author:LU Yuhan,born in 1999,postgraduate.Her main research interests include image security retrieval and so on.
    CHEN Liquan,born in 1976,Ph.D,professor,Ph.D supervisor,is a member of China Computer Federation.His main research interests include information security,cryptography and network security protocol,etc.
  • Supported by:
    National Key R & D Program of China(2020YFE0200600)and National Natural Science Foundation of China(62002058).

PDF (PC)

2208

Abstract: With the rapid development of smart devices,content-based image retrieval technology(CBIR) on the cloud is becoming increasingly popular.However,image retrieval on a semi-honest cloud server carries the risk of compromising user privacy.To prevent personal privacy from being compromised,users encrypt their images before outsourcing them to the cloud,but existing CBIR schemes on plaintext domains are ineffective for searching encrypted image data.To solve these problems,an efficient encrypted image content retrieval scheme based on approximate number homomorphism is proposed in the paper,which can quickly achieve image search without continuous user interaction while protecting user privacy.Firstly,feature extraction of image sets using approximate number homomorphism neural network can ensure that the parameters of the network model and the image set data are not leaked to the cloud server.Secondly,a new neural network partitioning method is also proposed to reduce the homomorphic encryption multiplication depth and improve the model operation efficiency,and also construct the index using hierarchical navigable small world(HNSW) algorithm to achieve efficient image retrieval.In addition,homomorphic encryption is used to guarantee the security of image data transmission process and symmetric encryption algorithm is used to guarantee the security of storage stage.Finally,the security and efficiency of the scheme are proved by experimental comparison and security analysis.Experimental results show that the scheme is IND-CCA,and the number of multiplications of homomorphic encryption in this scheme is at most 3 times while guaranteeing the image privacy,which far exceeds the existing schemes in terms of retrieval accuracy and at least 100 times higher than the existing schemes in terms of retrieval time complexity,achieving a balance of retrieval accuracy and efficiency.

Key words: Approximately homomorphic, Content-based image retrieval, Neural Network, Hierarchical navigable small world algorithm, Efficient search

CLC Number: 

  • TP391.41
[1]LI X,YANG J,MA J.Recent developments of content-basedimage retrieval(CBIR)[J].Neurocomputing,2021,452:675-689.
[2]HE Y,CHEN L,NI Y,et al.Privacy protection scheme for edge computing based on function encryption[C]//2021 International Conference on Networking and Network Applications(NaNA).IEEE,2021:131-135.
[3]LIU W,WU D J.Research progress on privacy protection ofmedical information[J].Software,2020,41(5):74-79.
[4]2020 Data Breach Incident Report in the U.S.Healthcare Industry [EB/OL].www.mchz.com.cn.
[5]WANG H,XIA Z,FEI J,et al.An AES-based secure image retrieval scheme using random mapping and BOW in cloud computing[J].IEEE Access,2020,8:61138-61147.
[6]AGRAWAL R,KIERNAN J,SRIKANT R,et al.Order preserving encryption for numeric data[C]//Proceedings of the 2004 ACM SIGMOD International Conference on Management of Data.2004:563-574.
[7]FURUKAWA J.Request-based comparable encryption[C]//European symposium on research in computer security.Berlin:Springer,2013:129-146.
[8]CHEN P,YE J,CHEN X.Efficient request-based comparable encryption scheme based on sliding window method[J].Soft Computing,2016,20:4589-4596.
[9]ZOU Q,WANG J,YE J,et al.Efficient and secure encryptedimage search in mobile cloud computing[J].Soft Computing,2017,21:2959-2969.
[10]QIN Z,YAN J,REN K,et al.Towards efficient privacy-preserving image feature extraction in cloud computing[C]//Procee-dings of the 22nd ACM International Conference on Multimedia.2014:497-506.
[11]FENG Q,LI P,LU Z,et al.DHAN:Encrypted JPEG image retrieval via DCT histograms-based attention networks[J].Applied Soft Computing,2023,133:109935.
[12]ZHANG C,LI J,WANG S,et al.An encrypted medical image retrieval algorithm based on DWT-DCT frequency domain[C]//2017 IEEE 15th International Conference on Software Enginee-ring Research,Management and Applications(SERA).IEEE,2017:135-141.
[13]GILAD-BACHRACH R,DOWLIN N,LAINE K,et al.Cryp-tonets:Applying neural networks to encrypted data with high throughput and accuracy[C]//International Conference on Machine Learning.PMLR,2016:201-210.
[14]CHOU E,BEAL J,LEVY D,et al.Faster cryptonets:Leveraging sparsity for real-world encrypted inference[J].arXiv:1811.09953,2018.
[15]JUVEKAR C,VAIKUNTANATHAN V,CHANDRAKASAN A.{GAZELLE}:A low latency framework for secure neural network inference[C]//27th {USENIX} Security Symposium({USENIX} Security 18).2018:1651-1669.
[16]PERETEANU G L,ALANSARY A,PASSERAT-PALMBACHJ.Split HE:Fast secure inference combining split lear-ning and homomorphic encryption[J].arXiv:2202.13351,2022.
[17]CHEON J H,KIM A,KIM M,et al.Homomorphic encryption for arithmetic of approximate numbers[C]//Advances in Cryptology-ASIACRYPT 2017:23rd International Conference on the Theory and Applications of Cryptology and Information Security.Springer International Publishing,2017:409-437.
[18]GALLEGO A J,RICO-JUAN J R,VALERO-MAS J J.Efficient k-nearest neighbor search based on clustering and adaptive k values[J].Pattern Recognition,2022,122:108356.
[19]LI W,ZHANG Y,SUN Y,et al.Approximate nearest neighbor search on high dimensional data—experiments,analyses,and improvement[J].IEEE Transactions on Knowledge and Data Engineering,2019,32(8):1475-1488.
[20]BELARBI M A,MAHMOUDI S,BELALEM G,et al.A NewComparative Study of Dimensionality Reduction Methods in Large-Scale Image Retrieval[J].Big Data and Cognitive Computing,2022,6(2):54.
[21]THAKUR N,REIMERS N,LIN J.Domain adaptation for me-mory-efficient dense retrieval[J].arXiv:2205.11498,2022.
[22]MALKOV Y A,YASHUNIN D A.Efficient and robust appro-ximate nearest neighbor search using hierarchical navigable small world graphs[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2018,42(4):824-836.
[23]IOFFE S,SZEGEDY C.Batch normalization:Accelerating deep network training by reducing internal covariate shift[C]//International Conference on Machine Learning.PMLR,2015:448-456.
[24]HESAMIFARD E,TAKABI H,GHASEMI M.Cryptodl:Deep neural networks over encrypted data[J].arXiv:1711.05189,2017.
[25]WANG Y,CHEN L,WU G,et al.Efficient and secure content-based image retrieval with deep neural networks in the mobile cloud computing[J].Computers & Security,2023,128:103163.
[26]CHENG K,FU J,SHEN Y,et al.Manto:A Practical and Secure Inference Service of Convolutional Neural Networks for IoT[J].IEEE Internet of Things Journal,doi:10.1109/JIOT.2023.3251982.
[27]SRINIVASAN W Z,AKSHAYARAM P,ADA P R.DELPHI:A cryptographic inference service for neural networks[C]//Proceedings of 29th USENIX Security.2019:2505-2522.
[28]XIA Z,XIONG N N,VASILAKOS A V,et al.EPCBIR:An efficient and privacy-preserving content-based image retrieval scheme in cloud computing[J].Information Sciences,2017,387:195-204.
[29]WANG Z,QIN J,XIANG X,et al.A privacy-preserving andtraitor tracking content-based image retrieval scheme in cloud computing[J].Multimedia Systems,2021,27:403-415.
[30]LEE J W,KANG H,LEE Y,et al.Privacy-preserving machine learning with fully homomorphic encryption for deep neural network[J].arXiv:2106.07229,2021.
[31]RATHEE D,RATHEE M,KUMAR N,et al.CrypTFlow2:Practical 2-party secure inference[C]//Proceedings of the 2020 ACM SIGSAC Conference on Computer and Communications Security.2020:325-342.
[32]HUANG Z,LU W,HONG C,et al.Cheetah:Lean and Fast Secure {Two-Party} Deep Neural Network Inference[C]//31st USENIX Security Symposium(USENIX Security 22).2022:809-826.
[33]HASSAN A,LIU F,WANG F,et al.Secure content basedimage retrieval for mobile users with deep neural networks in the cloud[J].Journal of Systems Architecture,2021,116:102043.
[34]WANG Z,QIN J,XIANG X,et al.A privacy-preserving andtraitor tracking content-based image retrieval scheme in cloud computing[J].Multimedia Systems,2021,27:403-415.
[35]SHEN M,CHENG G,ZHU L,et al.Content-based multi-source encrypted image retrieval in clouds with privacy preservation[J].Future Generation Computer Systems,2020,109:621-632.
[1] HUANG Shuxin, ZHANG Quanxin, WANG Yajie, ZHANG Yaoyuan, LI Yuanzhang. Research Progress of Backdoor Attacks in Deep Neural Networks [J]. Computer Science, 2023, 50(9): 52-61.
[2] YI Qiuhua, GAO Haoran, CHEN Xinqi, KONG Xiangjie. Human Mobility Pattern Prior Knowledge Based POI Recommendation [J]. Computer Science, 2023, 50(9): 139-144.
[3] LI Haiming, ZHU Zhiheng, LIU Lei, GUO Chenkai. Multi-task Graph-embedding Deep Prediction Model for Mobile App Rating Recommendation [J]. Computer Science, 2023, 50(9): 160-167.
[4] ZHU Ye, HAO Yingguang, WANG Hongyu. Deep Learning Based Salient Object Detection in Infrared Video [J]. Computer Science, 2023, 50(9): 227-234.
[5] YI Liu, GENG Xinyu, BAI Jing. Hierarchical Multi-label Text Classification Algorithm Based on Parallel Convolutional Network Information Fusion [J]. Computer Science, 2023, 50(9): 278-286.
[6] HENG Hongjun, MIAO Jing. Fusion of Semantic and Syntactic Graph Convolutional Networks for Joint Entity and Relation Extraction [J]. Computer Science, 2023, 50(9): 295-302.
[7] TANG Shaosai, SHEN Derong, KOU Yue, NIE Tiezheng. Link Prediction Model on Temporal Knowledge Graph Based on Bidirectionally Aggregating Neighborhoods and Global Aware [J]. Computer Science, 2023, 50(8): 177-183.
[8] MA Weiwei, ZHENG Qinhong, LIU Shanshan. Study and Evaluation of Spiking Neural Network Model Based on Bee Colony Optimization [J]. Computer Science, 2023, 50(8): 221-225.
[9] LI Qiaojun, ZHANG Wen, YANG Wei. Fusion Neural Network-based Method for Predicting LncRNA-disease Association [J]. Computer Science, 2023, 50(8): 226-232.
[10] XIE Tonglei, DENG Li, YOU Wenlong, LI Ruilong. Analysis and Prediction of Cloud VM CPU Load Based on EMPC-BCGRU [J]. Computer Science, 2023, 50(8): 243-250.
[11] ZHAO Ran, YUAN Jiabin, FAN Lili. Medical Ultrasound Image Super-resolution Reconstruction Based on Video Multi-frame Fusion [J]. Computer Science, 2023, 50(7): 143-151.
[12] JIANG Linpu, CHEN Kejia. Self-supervised Dynamic Graph Representation Learning Approach Based on Contrastive Prediction [J]. Computer Science, 2023, 50(7): 207-212.
[13] ZHU Yuying, GUO Yan, WAN Yizhao, TIAN Kai. New Word Detection Based on Branch Entropy-Segmentation Probability Model [J]. Computer Science, 2023, 50(7): 221-228.
[14] LI Rongchang, ZHENG Haibin, ZHAO Wenhong, CHEN Jinyin. Data Reconstruction Attack for Vertical Graph Federated Learning [J]. Computer Science, 2023, 50(7): 332-338.
[15] XIONG Haojie, WEI Yi. Study on Multibeam Sonar Elevation Data Prediction Based on Improved CNN-BP [J]. Computer Science, 2023, 50(6A): 220100161-4.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
渝ICP备16013121号-4
Add:18# Honghu West Rd., Yubei ,Chongqing,China    Post Code: 401121
Tel: 023-63500828/023-67039612/023-67039623
E-mail: jsjkx12@163.com
Powered by Beijing Magtech Co., Ltd.