Modeling an efficient authentic provable data possession model using legacy filter model for IOT and cloud environment

ABSTRACT Internet of Things (IoT) is extensively adopted to manage everyday life. Data is gathered from IoT devices cloud computing is inevitable to store and analyze the data. The storage over the cloud is also not owned by the end-user. Thus, it is not so feasible. Therefore, two diverse issues are directly connected with the verification of data integrity, i.e. the incoming data should be verified and the verification process is performed. Various prevailing approaches are used for performing data integrity verification over the trusted party and nodes with proper resources. Moreover, it is highly complex to apply different prevalent research methods to IoT devices with constrained resources. This work concentrates on performing secure cloud-based storage over an IoT environment using authentic provable data possession (APDP) using the Legacy filtering model (APDP-LFM). The major contribution is the data possession and filter process to reduce the computational complexity. The experimentation is performed using a MATLAB environment, and the outcomes demonstrate that the proposed model preserves computational time and no complexity over the verification process. This model helps avoid False Positives and efficiently works for the enormous amount of incoming data over the IoT environment.