Secured Fine-Grained Selective Access to Outsourced Cloud Data in IoT Environments
| Autor: | Emmanuel Boateng Sifah, Jianbin Gao, Kwame Opuni-Boachie Obour Agyekum, Mohsen Guizani, Abla Smahi, Xiaojiang Du, Hu Xia, Kingsley Nketia Acheampong, Qi Xia |
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| Rok vydání: | 2019 |
| Předmět: |
key-policy attribute-based encryption (KP-ABE)
Security analysis Blockchain Computer Networks and Communications Computer science Data management Cloud computing Access control 02 engineering and technology Encryption Computer security computer.software_genre Ciphertext 0202 electrical engineering electronic engineering information engineering business.industry 020206 networking & telecommunications fine-grained access control Computer Science Applications Data access Hardware and Architecture Signal Processing Scalability 020201 artificial intelligence & image processing smart contract business computer Information Systems |
| Zdroj: | IEEE Internet of Things Journal. 6:10749-10762 |
| ISSN: | 2372-2541 |
| DOI: | 10.1109/jiot.2019.2941638 |
| Popis: | With the vast increase in data transmission due to a large number of information collected by devices, data management, and security has been a challenge for organizations. Many data owners (DOs) outsource their data to cloud repositories due to several economic advantages cloud service providers present. However, DOs, after their data are outsourced, do not have complete control of the data, and therefore, external systems are incorporated to manage the data. Several kinds of research refer to the use of encryption techniques to prevent unauthorized access to data but prove to be deficient in providing suitable solutions to the problem. In this article, we propose a secure fine-grain access control system for outsourced data, which supports read and write operations to the data. We make use of an attribute-based encryption (ABE) scheme, which is regarded as a suitable scheme to achieve access control for security and privacy (confidentiality) of outsourced data. This article considers different categories of data users, and make provisions for distinct access roles and permissible actions on the outsourced data with dynamic and efficient policy updates to the corresponding ciphertext in cloud repositories. We adopt blockchain technologies to enhance traceability and visibility to enable control over outsourced data by a DO. The security analysis presented demonstrates that the security properties of the system are not compromised. Results based on extensive experiments illustrate the efficiency and scalability of our system. - 2014 IEEE. Manuscript received May 5, 2019; revised July 6, 2019 and August 21, 2019; accepted September 4, 2019. Date of publication September 16, 2019; date of current version December 11, 2019. This work was supported in part by the National Key Research and Development Project under Grant 2017YFB0802900, in part by the Program of International Science and Technology Cooperation and Exchange of Sichuan Province under Grant 2017HH0028, Grant 2018HH0102, and Grant 2019YFH0014, in part by the Sichuan Science and Technology Program under Grant 2017CC0071, in part by the Natural Science Foundation of China under Grant 61572115, and in part by CCF-Tencent Open Research Fund. (Corresponding author: Jianbin Gao.) Q. Xia is with the Center for Cyber Security, University of Electronic Science and Technology of China, Chengdu 610054, China (e-mail: xiaqi@uestc.edu.cn). Scopus |
| Databáze: | OpenAIRE |
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