Data Sharing Attribute-Based Secure with Efficient Revocation in Cloud Computing
Title | Data Sharing Attribute-Based Secure with Efficient Revocation in Cloud Computing |
Publication Type | Conference Paper |
Year of Publication | 2020 |
Authors | Elavarasan, G., Veni, S. |
Conference Name | 2020 International Conference on Computing and Information Technology (ICCIT-1441) |
Date Published | Sept. 2020 |
Publisher | IEEE |
ISBN Number | 978-1-7281-2680-7 |
Keywords | Authorization, cloud computing, composability, Computer science, Data encryption key, data privacy, Efficient revocation, Encryption, Human Behavior, information technology, Metrics, process control, pubcrawl, resilience, Resiliency, Secure File Sharing, security analysis |
Abstract | In recent days, cloud computing is one of the emerging fields. It is a platform to maintain the data and privacy of the users. To process and regulate the data with high security, the access control methods are used. The cloud environment always faces several challenges such as robustness, security issues and so on. Conventional methods like Cipher text-Policy Attribute-Based Encryption (CP-ABE) are reflected in providing huge security, but still, the problem exists like the non-existence of attribute revocation and minimum efficient. Hence, this research work particularly on the attribute-based mechanism to maximize efficiency. Initially, an objective coined out in this work is to define the attributes for a set of users. Secondly, the data is to be re-encrypted based on the access policies defined for the particular file. The re-encryption process renders information to the cloud server for verifying the authenticity of the user even though the owner is offline. The main advantage of this work evaluates multiple attributes and allows respective users who possess those attributes to access the data. The result proves that the proposed Data sharing scheme helps for Revocation under a fine-grained attribute structure. |
URL | https://ieeexplore.ieee.org/document/9213790 |
DOI | 10.1109/ICCIT-144147971.2020.9213790 |
Citation Key | elavarasan_data_2020 |