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Achieving Secure, Scalable, and Fine-grained Data Access Control in Cloud Computing
Abstract
Cloud computing is an emerging computing paradigm in which resources of the computing infrastructure are provided as services over the Internet. As promising as it is, this paradigm also brings forth many new challenges for data security and access control when users outsource sensitive data for sharing on cloud servers, which are not within the same trusted domain as data owners. To keep sensitive user data confidential against untrusted servers, existing solutions usually apply cryptographic methods by disclosing data decryption keys only to authorized users. However, in doing so, these solutions inevitably introduce a heavy computation overhead on the data owner for key distribution and data management when fine-grained data access control is desired, and thus do not scale well. The problem of simultaneously achieving fine-grainedness, scalability, and data confidentiality of access control actually still remains unresolved. This paper addresses this challenging open issue by, on one hand, defining and enforcing access policies based on data attributes, and, on the other hand, allowing the data owner to delegate most of the computation tasks involved in fine-grained data access control to untrusted cloud servers without disclosing the underlying data contents. We achieve this goal by exploiting and uniquely combining techniques of attribute-based encryption (ABE), proxy re-encryption, and lazy re-encryption. Our proposed scheme also has salient properties of user access privilege confidentiality and user secret key accountability. Extensive analysis shows that our proposed scheme is highly efficient and provably secure under existing security models.
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Cited by
A survey on security challenges in cloud computing: issues, threats, and solutions
Tabrizchi, H., & Kuchaki Rafsanjani, M. (2020) · The Journal of Supercomputing · doi:10.1007/s11227-020-03213-1 · Cited by 538
Data security and privacy-preserving in edge computing paradigm: survey and open issues
Zhang, J., Chen, B., Zhao, Y., Cheng, X., & Hu, F. (2018) · IEEE Access · doi:10.1109/access.2018.2820162 · Cited by 514
Privacy-preserving multi-keyword fuzzy search over encrypted data in the cloud
Wang, B., Yu, S., Lou, W., & Hou, Y. T. (2014) · IEEE INFOCOM 2014 - IEEE Conference on Computer Communications · doi:10.1109/infocom.2014.6848153 · Cited by 391
Self-citationCybersecurity for industrial control systems: A survey
Bhamare, D., Zolanvari, M., Erbad, A., Jain, R., Khan, K., & Meskin, N. (2020) · Computers & Security · doi:10.1016/j.cose.2019.101677 · Cited by 394
Towards secure mobile cloud computing: a survey
Khan, A. N., Mat Kiah, M. L., Khan, S. U., & Madani, S. A. (2013) · Future Generation Computer Systems · doi:10.1016/j.future.2012.08.003 · Cited by 368
Metadata
- Authors
- Yu, S., Wang, C., Ren, K., & Lou, W.
- Venue
- 2010 Proceedings IEEE INFOCOM
- Publisher
- IEEE
- Published
- 2010-03
- Pages
- 1-9
- OpenAlex
- W2116626915
- Cited by
- 1,602
- References
- 0
- FWCI
- 73.53
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Yu, S., Wang, C., Ren, K., & Lou, W. (2010). Achieving Secure, Scalable, and Fine-grained Data Access Control in Cloud Computing. 2010 Proceedings IEEE INFOCOM. https://doi.org/10.1109/infcom.2010.5462174
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