Title:
SECURE AND EFFICIENT DATA MANAGEMENT FOR HEALTHCARE IOT DEVICES IN CLOUD-ENABLED SYSTEMS USING SERPENT ENCRYPTION

Authors:
Raj Kumar Gudivaka, Rajya Lakshmi Gudivaka and Karthick.M, India

Abstract:
The increasing adoption of Internet of Things (IoT) devices in healthcare has significantly improved patient monitoring and care management, enabling collection of critical health data. However, challenges remain in ensuring the secure transfer of sensitive data, managing computational overhead, and optimizing data transmission efficiency in cloud-enabled healthcare systems. This paper presents a framework that addresses these challenges by enhancing security and optimizing the transfer of healthcare data in IoT systems. The system begins with collecting data from healthcare IoT devices, such as wearable health monitors and patient monitoring systems. Then, the collected data is scaled using Robust Scaler, which helps in mitigating the influence of outliers, ensuring that the data is normalized while maintaining robustness. Categorical data is handled by Label Encoding, converting non-numeric categories into numeric labels. After preprocessing, the data undergoes encryption using the Serpent cipher, which provides secure encryption, ensuring that sensitive healthcare data is protected during storage or transfer. Finally, the processed and encrypted data is securely transferred to the cloud platform for storage and processing. Experimental results demonstrate that as key size increases from 128 bits to 256 bits, the Serpent encryption strength improves, reaching approximately 98%, while transmission latency rises from 50 ms for 1 MB of data to 3800 ms for 100 MB. This work by develops a secure, efficient, and scalable framework that ensures the privacy of healthcare data while minimizing latency in IoT cloud systems.