| dc.contributor | 資科系 | |
| dc.creator (作者) | 曾一凡 | |
| dc.creator (作者) | Tseng, Yi-Fan | |
| dc.creator (作者) | Gao, Shih-Jie | |
| dc.date (日期) | 2022-01 | |
| dc.date.accessioned | 6-Feb-2023 14:30:52 (UTC+8) | - |
| dc.date.available | 6-Feb-2023 14:30:52 (UTC+8) | - |
| dc.date.issued (上傳時間) | 6-Feb-2023 14:30:52 (UTC+8) | - |
| dc.identifier.uri (URI) | http://nccur.lib.nccu.edu.tw/handle/140.119/143306 | - |
| dc.description.abstract (摘要) | With the rise of technology in recent years, more people are studying distributed system architecture, such as the e-government system. The advantage of this architecture is that when a single point of failure occurs, it does not cause the system to be invaded by other attackers, making the entire system more secure. On the other hand, inner product encryption (IPE) provides fine-grained access control, and can be used as a fundamental tool to construct other cryptographic primitives. Lots of studies for IPE have been proposed recently. The first and only existing decentralized IPE was proposed by Michalevsky and Joye in 2018. However, some restrictions in their scheme may make it impractical. First, the ciphertext size is linear to the length of the corresponding attribute vector; second, the number of authorities should be the same as the length of predicate vector. To cope with the aforementioned issues, we design the first decentralized IPE with constant-size ciphertext. The security of our scheme is proven under the ℓ-DBDHE assumption in the random oracle model. Compared with Michalevsky and Joye’s work, ours achieves better efficiency in ciphertext length and encryption/decryption cost. | |
| dc.format.extent | 99 bytes | - |
| dc.format.mimetype | text/html | - |
| dc.relation (關聯) | Applied Sciences, Vol.12, No.2, 636 | |
| dc.subject (關鍵詞) | inner product encryption; decentralized inner product encryption; constant-size ciphertext | |
| dc.title (題名) | Decentralized Inner-Product Encryption with Constant-Size Ciphertext | |
| dc.type (資料類型) | article | |
| dc.identifier.doi (DOI) | 10.3390/app12020636 | |
| dc.doi.uri (DOI) | https://doi.org/10.3390/app12020636 | |
