Abstract

ABSTRACT Due to the Internet of Things (IoT) widespread adoption, data traffic to cloud servers for analysis has surged, impacting IoT system latency. Fog Computing emerged as a solution, bringing processing capabilities closer to data generation points, reducing data sent to the cloud, and improving response times. However, it intensifies security concerns due to the proximity of sensitive data to users and limited node computational resources. This research aims to study encryption and data verification algorithms using various datasets and the cryptography software OpenSSL. Testing is performed on Raspberry Pi hardware, facilitating the implementation of Fog nodes. Metrics such as CPU, memory, and energy consumption are evaluated using scripts. Results show that data type does not influence algorithm choice, and patterns related to data size behaviour are identified, aiding in defining security strategies.

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