Author : Sreekar Peddi, Sai Sathish Kethu, Durai Rajesh Natarajan and Karthick.M

The increasingly rapid growth of IoT devices has resulted in an unprecedented rise in the amount of data from these sources. Thus, there will be an utmost need for efficient and secured handling of all increasing volumes and varieties of data at different speeds. Data get collected from heterogeneous sensors and are then preprocessed using Z-score normalization and k-NN imputation methods to increase the quality and consistency of the data. The proposed solution is based on an edge-to-cloud architecture implementing lightweight encryption, robust data preprocessing, and elastic cloud storage to solve the problems of latency, scalability, and confidentiality of data. The encryption of data is performed by the ChaCha20-Poly1305 algorithm, which is fast and secure, custom-made for IoT applications with resource constraints. The encrypted data will be stored in cloud infrastructure that scales dynamically as per workload requirements. The performance evaluation assures the trustworthiness of the solution in managing massive IoT operations, reducing latency, maintaining data integrity, and its ability to scale. The maximum latency recorded was 220 ms at a high device load; encryption time scaled linearly with increasing plaintext size to 90 seconds, whereas scalability remained above 95% with less than 0.2% packet loss rate.

Keywords: Edge-to-Cloud Architecture, IoT Data Management, ChaCha20-Poly1305 Encryption, Z-score Normalization, Lightweight Security, Scalability, Cloud Storage.