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      A Secure and Lightweight Fine-Grained Data Sharing Scheme for Mobile Cloud Computing

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          Abstract

          With the explosion of various mobile devices and the tremendous advancement in cloud computing technology, mobile devices have been seamlessly integrated with the premium powerful cloud computing known as an innovation paradigm named Mobile Cloud Computing (MCC) to facilitate the mobile users in storing, computing and sharing their data with others. Meanwhile, Attribute Based Encryption (ABE) has been envisioned as one of the most promising cryptographic primitives for providing secure and flexible fine-grained “one to many” access control, particularly in large scale distributed system with unknown participators. However, most existing ABE schemes are not suitable for MCC because they involve expensive pairing operations which pose a formidable challenge for resource-constrained mobile devices, thus greatly delaying the widespread popularity of MCC. To this end, in this paper, we propose a secure and lightweight fine-grained data sharing scheme (SLFG-DSS) for a mobile cloud computing scenario to outsource the majority of time-consuming operations from the resource-constrained mobile devices to the resource-rich cloud servers. Different from the current schemes, our novel scheme can enjoy the following promising merits simultaneously: (1) Supporting verifiable outsourced decryption, i.e., the mobile user can ensure the validity of the transformed ciphertext returned from the cloud server; (2) resisting decryption key exposure, i.e., our proposed scheme can outsource decryption for intensive computing tasks during the decryption phase without revealing the user’s data or decryption key; (3) achieving a CCA security level; thus, our novel scheme can be applied to the scenarios with higher security level requirement. The concrete security proof and performance analysis illustrate that our novel scheme is proven secure and suitable for the mobile cloud computing environment.

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                Author and article information

                Journal
                Sensors (Basel)
                Sensors (Basel)
                sensors
                Sensors (Basel, Switzerland)
                MDPI
                1424-8220
                21 August 2020
                September 2020
                : 20
                : 17
                Affiliations
                [1 ]School of Software, Dalian University of Technology, Dalian 116024, China; lihaifeng8848@ 123456mail.dlut.edu.cn (H.L.); guohe@ 123456dlut.edu.cn (H.G.)
                [2 ]School of Electronic and Information Engineering, Lanzhou City University, Lanzhou 730070, China
                [3 ]Guangxi Key Laboratory of Cryptography and Information Security, Guilin 541004, China; uestcfuxb@ 123456126.com
                [4 ]School of Cyberspace, Hangzhou Dianzi University, Hangzhou 310018, China
                [5 ]Guangdong Provincial Key Laboratory of Information Security Technology, Guangzhou 510275, China
                [6 ]College of Big Data and Internet, Shenzhen Technology University, Shenzhen 518118, China; wangcaifen@ 123456sztu.edu.cn
                [7 ]School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China; fagenli@ 123456uestc.edu.cn
                Author notes
                [* ]Correspondence: lanzhourm@ 123456163.com
                Article
                sensors-20-04720
                10.3390/s20174720
                7506934
                32825602
                © 2020 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

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