Partitioning-Based Data Sharing Approach for Data Integrity Verification in Distributed Fog Computing

Abstract

With the increasing popularity of the internet of things (IoT), fog computing has emerged as a unique cutting-edge approach along with cloud computing. This study proposes an approach for data integrity verification in fog computing that does not require metadata stored on the user side and can handle big data efficiently. In the proposed work, fuzzy clustering is used to cluster IoT data; dynamic keys are used to encrypt the clusters; and dynamic permutation is used to distribute encrypted clusters among fog nodes. During the process of data retrieval, fuzzy clustering and message authentication code (MAC) are used to verify the data integrity. Fuzzy clustering and dynamic primitives make the proposed approach more secure. The security analysis indicates that the proposed approach is resilient to various security attacks. Moreover, the performance analysis shows that the computation time of the proposed work is 50 times better than the existing tag regeneration scheme.