An Efficient Approach for Secured Data Transmission Between IoT and Cloud
DOI:
https://doi.org/10.37256/rrcs.2320232628Keywords:
Internet of Things (IoT), fog computing, cloud, data filtering, noisy data, data classification, k-nearest neighbor, complement naive Bayes, accuracyAbstract
The Internet of Things (IoT) network generates a lot of data and cloud servers collect that data. The server then analyzes the collected data and based on the findings, provides appropriate intelligent services to users as a result. If there is any faulty data while the server analyzes the collected data, distorted results will be created. The data captured from IoT contains lots of heterogeneous as well as suspicious data, so cleaning, filtering, and clustering of it must be done before sending it to the server, otherwise it will unnecessarily create overhead on the server. The proposed system consists of a filtering and clustering mechanism for the data collected from IoT devices so that integrated data is transferred to the cloud server which will reduce its computational load. In the proposed system, the fog computing layer is used as an interface between IoT and cloud computing layer where data filtering and clustering take place to reduce network traffic and latency. The ultimate aim is to provide security for data transmission between IoT and the cloud.
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Copyright (c) 2023 Shatakshi Kokate, Urmila Shrawankar
This work is licensed under a Creative Commons Attribution 4.0 International License.