Fully Secure Functional Encryption: Attribute-Based Encryption and (Hierarchical) Inner Product Encryption
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Jayasinghe et al. applied machine learning to a node trust evaluation framework, implemented unsupervised-learning-based data credibility labeling, and established a trust prediction model that improves trust evaluation accuracy and the ability to identify trusted interactions.
“As early as 2018, Jayasinghe U and others [46] and others applied machine learning technology to the node trust evaluation framework, implemented a data credibility labeling method based on unsupervised learning technology, and based on this node trust labeling method.The corresponding trust prediction model is established, which not only improves the accuracy of the trust evaluation algorithm but”
From A Survey on Zero Trust Architecture: Challenges and Future Trends (2022) · cites this paper as [46]
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DAC-MACS: Effective Data Access Control for Multiauthority Cloud Storage Systems
Yang, K., Jia, X., Ren, K., Zhang, B., & Xie, R. (2013) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2013.2279531 · Cited by 310 · see citing works
A Survey on Zero Trust Architecture: Challenges and Future Trends
He, Y., Huang, D., Chen, L., Ni, Y., & Ma, X. (2022) · Wireless Communications and Mobile Computing · doi:10.1155/2022/6476274 · Cited by 260 · see citing works
“Direct revocation is introduced into ABE, which ensures that unrevoked users are not affected and do not need to update keys for users regularly.”
BackgroundInfluentialPrivacy preserving EHR system using attribute-based infrastructure
Narayan, S., Gagné, M., & Safavi-Naini, R. (2010) · Proceedings of the 2010 ACM workshop on Cloud computing security workshop · doi:10.1145/1866835.1866845 · Cited by 257 · see citing works
Ullah, S., Zheng, J., Din, N., Hussain, M. T., Ullah, F., & Yousaf, M. (2023) · Computer Science Review · doi:10.1016/j.cosrev.2022.100530 · Cited by 195 · see citing works
- Authors
- Lewko, A., Okamoto, T., Sahai, A., Takashima, K., & Waters, B.
- Affiliations
- The University of Texas at Austin (US)
- NTT (Japan) (JP)
- University of California, Los Angeles (US)
- Mitsubishi Electric (Japan) (JP)
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer Berlin Heidelberg
- Published
- 2010
- Pages
- 62-91
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W177444027
- Cited by
- 1,313
- References
- 0
- Citations by year
- 2026: 11 · 2025: 34 · 2024: 48 · 2023: 59 · 2022: 64 · 2021: 75 · 2020: 81 · 2019: 104 · 2018: 73 · 2017: 124 · 2016: 118 · 2015: 136 · 2014: 120 · 2013: 104 · 2012: 84
- FWCI
- 67.68
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- Lecture notes in computer science (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Cryptography and Data Security
- Physical Sciences › Computer Science › Information Systems › Cloud Data Security Solutions
- Physical Sciences › Computer Science › Artificial Intelligence › Quantum Information and Cryptography
- Keywords
- functional encryption, attribute-based encryption, predicate encryption, inner product encryption, attribute hiding, dual system encryption, bilinear pairings, composite order bilinear groups
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