| Title | Fully Accountable Data Sharing for Pay-As-You-Go Cloud Scenes |
| Publication Type | Journal Article |
| Year of Publication | 2019 |
| Authors | Wang, Ti, Ma, Hui, Zhou, Yongbin, Zhang, Rui, Song, Zishuai |
| Journal | IEEE Transactions on Dependable and Secure Computing |
| Pagination | 1–1 |
| ISSN | 2160-9209 |
| Keywords | Access Control, attribute-based encryption, cloud computing, compositionality, Computational modeling, Computer crime, Data models, data sharing, DDoS Attacks, Encryption, encryption audits, pay-as-you-go model, Predictive Metrics, pubcrawl, Resiliency |
| Abstract | Many enterprises and individuals prefer to outsource data to public cloud via various pricing approaches. One of the most widely-used approaches is the pay-as-you-go model, where the data owner hires public cloud to share data with data consumers, and only pays for the actually consumed services. To realize controllable and secure data sharing, ciphertext-policy attribute-based encryption (CP-ABE) is a suitable solution, which can provide fine-grained access control and encryption functionalities simultaneously. But there are some serious challenges when applying CP-ABE in pay-as-you-go. Firstly, the decryption cost in ABE is too heavy for data consumers. Secondly, ABE ciphertexts probably suffer distributed denial of services (DDoS) attacks, but there is no solution that can eliminate the security risk. At last, the data owner should audit resource consumption to guarantee the transparency of charge, while the existing method is inefficient. In this work, we propose a general construction named fully accountable ABE (FA-ABE), which simultaneously solves all the challenges by supporting all-sided accountability in the pay-as-you-go model. We formally define the security model and prove the security in the standard model. Also, we implement an instantiate construction with the self-developed library libabe. The experiment results indicate the efficiency and practicality of our construction. |
| DOI | 10.1109/TDSC.2019.2947579 |
| Citation Key | wang_fully_2019 |
Fully Accountable Data Sharing for Pay-As-You-Go Cloud Scenes