FRAUD FIND: FINANCIAL FRAUD DETECTION BY ANALYZING HUMAN BEHAVIOUR
| dc.contributor.author | SRIKANTHA T | |
| dc.date.accessioned | 2019-07-04T11:47:30Z | |
| dc.date.available | 2019-07-04T11:47:30Z | |
| dc.date.issued | 2019-07-04T11:47:30Z | |
| dc.description.abstract | Attribute-based Encryption (ABE) is regarded as a promising cryptographic conducting tool to guarantee data owners’ direct control over their data in public cloud storage. The earlier ABE schemes involve only one authority to maintain the whole attribute set, which can bring a single-point bottleneck on both security and performance. Subsequently, some multi-authority schemes are proposed, in which multiple authorities separately maintain disjoint attribute subsets. However, the single-point bottleneck problem remains unsolved. In this project, from another perspective, we conduct a threshold multi-authority CP-ABE access control scheme for public cloud storage, in which multiple authorities jointly manage a uniform attribute set. Taking advantage of threshold secret sharing, the master key can be shared among multiple authorities, and a legal user can generate his/her secret key by interacting with and authorities. Security and performance analysis results show that application is not only verifiable secure when less than authorities are compromised, but also robust when no less than authorities are alive in the system. Furthermore, by efficiently combining the traditional multi-authority scheme with the application, we construct a hybrid one, which satisfies the scenario of attributes coming from different authorities as well as achieving security and system-level robustness. | en_US |
| dc.identifier.uri | http://hdl.handle.net/123456789/10936 | |
| dc.language.iso | en | en_US |
| dc.subject | 1NZ17MCA84 | en_US |
| dc.title | FRAUD FIND: FINANCIAL FRAUD DETECTION BY ANALYZING HUMAN BEHAVIOUR | en_US |
| dc.type | Other | en_US |