Control Cloud Data Access Privilege and Anonymity With Fully Anonymous Attribute-Based Encryption. Jung, T., Li, X., Wan, Z., & Wan, M. IEEE Transactions on Information Forensics and Security, 10(1):190-199, IEEE, 1, 2015.
Control Cloud Data Access Privilege and Anonymity With Fully Anonymous Attribute-Based Encryption [link]Website  abstract   bibtex   
Cloud computing is a revolutionary computing paradigm, which enables flexible, on-demand, and low-cost usage of computing resources, but the data is outsourced to some cloud servers, and various privacy concerns emerge from it. Various schemes based on the attribute-based encryption have been proposed to secure the cloud storage. However, most work focuses on the data contents privacy and the access control, while less attention is paid to the privilege control and the identity privacy. In this paper, we present a semianonymous privilege control scheme AnonyControl to address not only the data privacy, but also the user identity privacy in existing access control schemes. AnonyControl decentralizes the central authority to limit the identity leakage and thus achieves semianonymity. Besides, it also generalizes the file access control to the privilege control, by which privileges of all operations on the cloud data can be managed in a fine-grained manner. Subsequently, we present the AnonyControl-F, which fully prevents the identity leakage and achieve the full anonymity. Our security analysis shows that both AnonyControl and AnonyControl-F are secure under the decisional bilinear Diffie-Hellman assumption, and our performance evaluation exhibits the feasibility of our schemes.
@article{
 title = {Control Cloud Data Access Privilege and Anonymity With Fully Anonymous Attribute-Based Encryption},
 type = {article},
 year = {2015},
 identifiers = {[object Object]},
 keywords = {access-control,anonymity,cloud,crypto,security},
 pages = {190-199},
 volume = {10},
 websites = {http://dx.doi.org/10.1109/tifs.2014.2368352},
 month = {1},
 publisher = {IEEE},
 id = {f36cb02d-0b11-3ec8-8934-8767914507a8},
 created = {2018-07-12T21:31:24.281Z},
 file_attached = {false},
 profile_id = {f954d000-ce94-3da6-bd26-b983145a920f},
 group_id = {b0b145a3-980e-3ad7-a16f-c93918c606ed},
 last_modified = {2018-07-12T21:31:24.281Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 citation_key = {jung:cloud},
 source_type = {article},
 notes = {BUT SEE ERRORS noted in this follow-up comment: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7360926 and rebuttal from the authors: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7398216 which, combined, improves the original scheme.},
 private_publication = {false},
 abstract = {Cloud computing is a revolutionary computing paradigm, which enables flexible, on-demand, and low-cost usage of computing resources, but the data is outsourced to some cloud servers, and various privacy concerns emerge from it. Various schemes based on the attribute-based encryption have been proposed to secure the cloud storage. However, most work focuses on the data contents privacy and the access control, while less attention is paid to the privilege control and the identity privacy. In this paper, we present a semianonymous privilege control scheme AnonyControl to address not only the data privacy, but also the user identity privacy in existing access control schemes. AnonyControl decentralizes the central authority to limit the identity leakage and thus achieves semianonymity. Besides, it also generalizes the file access control to the privilege control, by which privileges of all operations on the cloud data can be managed in a fine-grained manner. Subsequently, we present the AnonyControl-F, which fully prevents the identity leakage and achieve the full anonymity. Our security analysis shows that both AnonyControl and AnonyControl-F are secure under the decisional bilinear Diffie-Hellman assumption, and our performance evaluation exhibits the feasibility of our schemes.},
 bibtype = {article},
 author = {Jung, Taeho and Li, Xiang-Yang and Wan, Zhiguo and Wan, Meng},
 journal = {IEEE Transactions on Information Forensics and Security},
 number = {1}
}

Downloads: 0