The DOI matches its Crossref record; 39 of the 39 references it cites were found in a registry or an index.
Achieving Searchable and Privacy-Preserving Data Sharing for Cloud-Assisted E-Healthcare System
Abstract
The integration of wearable wireless devices and cloud computing in e-health systems has significantly improved their effectiveness and availability. Patients can upload their personal health information (PHI) files to the cloud, from where the health service providers (HSPs) can obtain appropriate information to determine the health state. This system not only reduces the costs associated to healthcare but also provides timely diagnosis to save lives. However, a number of privacy concerns arise while sharing sensitive information. In this paper, we propose a novel privacy-preserving patient health information sharing scheme, which allows HSPs to access and search PHI files in a secure yet efficient manner. We make use of the searchable encryption technique with keyword range search and multikeyword search. The proposed privacy-preserving equality test protocol allows different types of numeric comparison searches on encrypted data. We also use a variant of bloom filter and message authentication code to classify PHI files, filter false data, and check integrity of search results. The simulations on real-world and synthetic data show the feasibility and efficiency of the system, and security analysis proves the privacy-preservation properties.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“Furthermore, by using an inference attack by the malicious user, the adversary can get what kind of information is being shared.This might include blood samples, type of disease and other relevant data [50].”
From Federated Learning for Privacy Preservation in Smart Healthcare Systems: A Comprehensive Survey (2023) · cites this paper as [50]
Citations
Cites
Practical techniques for searches on encrypted data
Song, D., Wagner, D. A., & Perrig, A. (2002) · doi:10.1109/secpri.2000.848445 · Cited by 3,376
Secure Ranked Keyword Search over Encrypted Cloud Data
Wang, C., Cao, N., Li, J., Ren, K., & Lou, W. (2010) · IEEE International Conference on Distributed Computing Systems (ICDCS) · doi:10.1109/icdcs.2010.34 · Cited by 742
Dynamic Searchable Encryption in Very-Large Databases: Data Structures and Implementation
Cash, D., Jaeger, J., Jarecki, S., Jutla, C. S., Krawczyk, H., Roşu, M., & Steiner, M. (2014) · Network and Distributed System Security Symposium · doi:10.14722/ndss.2014.23264 · Cited by 692
Parallel and Dynamic Searchable Symmetric Encryption
Kamara, S., & Papamanthou, C. (2013) · Lecture notes in computer science · doi:10.1007/978-3-642-39884-1_22 · Cited by 532
VABKS: Verifiable attribute-based keyword search over outsourced encrypted data
Zheng, Q., Xu, S., & Ateniese, G. (2014) · doi:10.1109/infocom.2014.6847976 · Cited by 506
A Lightweight Privacy-Preserving Data Aggregation Scheme for Fog Computing-Enhanced IoT
Lu, R., Heung, K., Lashkari, A. H., & Ghorbani, A. A. (2017) · IEEE Access · doi:10.1109/access.2017.2677520 · Cited by 478
Secure attribute-based data sharing for resource-limited users in cloud computing
Li, J., Zhang, Y., Chen, X., & Xiang, Y. (2017) · Computers & Security · doi:10.1016/j.cose.2017.08.007 · Cited by 461
Authorized Private Keyword Search over Encrypted Data in Cloud Computing
Li, M., Yu, S., Cao, N., & Lou, W. (2011) · Proceedings of the ... International Conference on Distributed Computing Systems/Proceedings of the International Conference on Distributed Computing Systems · doi:10.1109/icdcs.2011.55 · Cited by 327
Dynamic Searchable Encryption via Blind Storage
Naveed, M., Prabhakaran, M., & Gunter, C. A. (2014) · Proceedings - IEEE Symposium on Security and Privacy/Proceedings of the ... IEEE Symposium on Security and Privacy · doi:10.1109/sp.2014.47 · Cited by 311
Firouzi, F., Rahmani, A. M., Mankodiya, K., Badaroglu, M., Merrett, G. V., Wong, P., & Farahani, B. (2017) · Future Generation Computer Systems · doi:10.1016/j.future.2017.09.016 · Cited by 303
An Efficient Privacy-Preserving Outsourced Calculation Toolkit With Multiple Keys
Liu, X., Deng, R. H., Choo, K. R., & Weng, J. (2016) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2016.2573770 · Cited by 263
A lightweight multi-layer authentication protocol for wireless body area networks
Shen, J., Chang, S., Shen, J., Liu, Q., & Sun, X. (2016) · Future Generation Computer Systems · doi:10.1016/j.future.2016.11.033 · Cited by 258
Efficient and Privacy-Preserving Carpooling Using Blockchain-Assisted Vehicular Fog Computing
Li, M., Zhu, L., & Lin, X. (2018) · IEEE Internet of Things Journal · doi:10.1109/jiot.2018.2868076 · Cited by 229
Self-citationA reliable IoT system for Personal Healthcare Devices
Woo, M. W., Lee, J., & Park, K. (2017) · Future Generation Computer Systems · doi:10.1016/j.future.2017.04.004 · Cited by 182
Li, W., Xue, K., Xue, Y., & Hong, J. (2015) · IEEE Transactions on Parallel and Distributed Systems · doi:10.1109/tpds.2015.2448095 · Cited by 153
Xue, K., Xue, Y., Hong, J., Li, W., Yue, H., Wei, D. S. L., & Hong, P. (2017) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2016.2647222 · Cited by 144
Zhang, C., Zhu, L., Xu, C. L., & Lu, R. (2017) · Future Generation Computer Systems · doi:10.1016/j.future.2017.09.002 · Cited by 141
Self-citationCombining Data Owner-Side and Cloud-Side Access Control for Encrypted Cloud Storage
Xue, K., Chen, W., Li, W., Hong, J., & Hong, P. (2018) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2018.2809679 · Cited by 131
File-Centric Multi-Key Aggregate Keyword Searchable Encryption for Industrial Internet of Things
Zhou, R., Zhang, X., Du, X., Wang, X., Yang, G., & Guizani, M. (2018) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2018.2794442 · Cited by 109
Boyle, E., Couteau, G., Gilboa, N., Ishai, Y., & Orrù, M. (2017) · ACM SIGSAC Conference on Computer and Communications Security (CCS) · doi:10.1145/3133956.3134107 · Cited by 105
Cloud-Assisted Mobile-Access of Health Data With Privacy and Auditability
Tong, Y., Sun, J., Chow, S. S. M., & Li, P. (2014) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2013.2294932 · Cited by 100
Miao, Y., Ma, J., Liu, X., Wei, F., Liu, Z., & Wang, X. A. (2016) · Journal of Medical Systems · doi:10.1007/s10916-016-0617-z · Cited by 90
Secure Phrase Search for Intelligent Processing of Encrypted Data in Cloud-Based IoT
Shen, M., Ma, B., Zhu, L., Du, X., & Xu, K. (2018) · IEEE Internet of Things Journal · doi:10.1109/jiot.2018.2871607 · Cited by 83
Self-citationJiang, R., Lu, R., & Choo, K. R. (2016) · Future Generation Computer Systems · doi:10.1016/j.future.2016.05.005 · Cited by 72
Anonymous Privacy-Preserving Task Matching in Crowdsourcing
Shu, J., Liu, X., Jia, X., Yang, K., & Deng, R. H. (2018) · IEEE Internet of Things Journal · doi:10.1109/jiot.2018.2830784 · Cited by 69
Secure deduplication storage systems supporting keyword search
Li, J., Chen, X., Xhafa, F., & Barolli, L. (2015) · Journal of Computer and System Sciences · doi:10.1016/j.jcss.2014.12.026 · Cited by 68
Verifiable Searchable Symmetric Encryption from Indistinguishability Obfuscation
Cheng, R., Yan, J., Guan, C., Zhang, F., & Ren, K. (2015) · ACM Asia Conference on Computer and Communications Security (ASIA CCS) · doi:10.1145/2714576.2714623 · Cited by 61
A Private Stable Matching Algorithm
Golle, P. (2006) · Lecture notes in computer science · doi:10.1007/11889663_5 · Cited by 47
Lightweight and Confidential Data Discovery and Dissemination for Wireless Body Area Networks
He, D., Chan, S., Zhang, Y., & Yang, H. (2014) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2013.2293620 · Cited by 45
Yang, L., Zheng, Q., & Fan, X. (2017) · doi:10.1109/infocom.2017.8056954 · Cited by 45
A multi-cloud based privacy-preserving data publishing scheme for the internet of things
Yang, L., Humayed, A. A., & Li, F. (2016) · doi:10.1145/2991079.2991127 · Cited by 30
Towards privacy protection and malicious behavior traceability in smart health
Zhang, Y., Li, J., Zheng, D., Chen, X., & Li, H. (2017) · Personal and Ubiquitous Computing · doi:10.1007/s00779-017-1047-8 · Cited by 26
Internet of Things: Security and privacy in a connected world
Li, J., Yan, Q., & Chang, V. I. C. (2017) · Future Generation Computer Systems · doi:10.1016/j.future.2017.09.017 · Cited by 14
Visual Analysis of Multimodal Movie Network Data Based on the Double-Layered View
Tang, Y., Yu, J., Li, C., & Fan, J. (2015) · International Journal of Distributed Sensor Networks · doi:10.1155/2015/906316 · Cited by 8
On the Security of a Modified Paillier Public-Key Primitive
Sakurai, K., & Takagi, T. (2002) · Lecture notes in computer science · doi:10.1007/3-540-45450-0_33 · Cited by 8
Diverse multi-keyword ranked search over encrypted cloud data supporting range query
Li, H., Ren, H., Yao, H., Chen, H., Xu, G., & Dai, Y. (2015) · IEEE/CIC International Conference on Communications in China (ICCC) · doi:10.1109/iccchina.2015.7448586 · Cited by 8
CPP: Towards comprehensive privacy preserving for query processing in information networks
Liu, C., Zhou, S., Hu, H., Tang, Y., Guan, J., & Ma, Y. (2018) · Information Sciences · doi:10.1016/j.ins.2018.08.010 · Cited by 7
Secure data access for wireless body sensor networks
Guan, Z., Yang, T., Du, X., & Guizani, M. (2016) · IEEE Wireless Communications and Networking Conference · doi:10.1109/wcnc.2016.7564976 · Cited by 6
Spectrum-Efficient Wireless Sensor Networks
Tang, S., Zhang, Y., Zhang, L., & Yu, R. (2015) · International Journal of Distributed Sensor Networks · doi:10.1155/2015/614680 · Cited by 4
Cited by
Sorted by citations
Federated learning for smart healthcare: A survey
Nguyen, D. C., Pham, Q.-V., Pathirana, P. N., Ding, M., Seneviratne, A., Lin, Z., Dobre, O., & Hwang, W.-J. (2023) · ACM Computing Surveys · doi:10.1145/3501296 · Cited by 827
Federated Learning for Privacy Preservation in Smart Healthcare Systems: A Comprehensive Survey
Ali, M., Naeem, F., Tariq, M., & Kaddoum, G. (2023) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2022.3181823 · Cited by 366
Federated learning for secure IoMT-applications in smart healthcare systems: A comprehensive review
Rani, S., Kataria, A., Kumar, S., & Tiwari, P. (2023) · Knowledge-Based Systems · doi:10.1016/j.knosys.2023.110658 · Cited by 228
Rasool, R. U., Ahmad, H. F., Rafique, W., Qayyum, A., & Qadir, J. (2022) · Journal of Network and Computer Applications · doi:10.1016/j.jnca.2022.103332 · Cited by 177
Decentralized Federated Learning for Healthcare Networks: A Case Study on Tumor Segmentation
Tedeschini, B. C., Savazzi, S., Stoklasa, R., Barbieri, L., Stathopoulos, I., Nicoli, M., & Serio, L. (2022) · IEEE Access · doi:10.1109/access.2022.3141913 · Cited by 176
Metadata
- Authors
- Xu, C., Wang, N., Zhu, L., Sharif, K., & Zhang, C.
- Affiliations
- Beijing Institute of Technology (CN)
- Venue
- IEEE Internet of Things Journal
- Published
- 2019-10
- Volume
- 6
- Issue
- 5
- Pages
- 8345-8356
- ISSN
- 2327-4662 (ISSN-L)
- 2372-2541
- OpenAlex
- W2945262612
- Cited by
- 105
- References
- 39
- Citations by year
- 2026: 4 · 2025: 4 · 2024: 15 · 2023: 31 · 2022: 28 · 2021: 17 · 2020: 6
- FWCI
- 5.88
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- IEEE Internet of Things Journal (publishedVersion)
- Funders
- National Natural Science Foundation of China (61402037, 61272512)
- Beijing Institute of Technology (2018CX20013)
- Topics
- Physical Sciences › Computer Science › Computer Networks and Communications › Cryptography and Data Security
- Physical Sciences › Computer Science › Information Systems › Cloud Data Security Solutions
- Physical Sciences › Computer Science › Information Systems › Blockchain Technology Applications and Security
- Keywords
- privacy-preserving data sharing, searchable encryption, searchable symmetric encryption, wearable devices, personal health data, Bloom filter, message authentication codes, data integrity
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
