Adaptive Multi-Layer Encryption for enhancing security in smart home IoT ecosystems

Abstract

The explosion of Internet of Things (IoT) devices in smart home environments has significantly improved the automation and user convenience while introducing complex security and privacy challenges. Current IoT devices have inherent resource constraints and often struggle to implement traditional encryption mechanisms such as Advanced Encryption Standard (AES) and Rivest-Shamir-Adleman (RSA), which demand a lot of computational resources and lack adaptability to emerging threats. This research addresses this security gap by developing an Adaptive Multi-Layer Encryption (AMLE) model specifically tailored for smart home IoT ecosystems. This study employed a prototype development methodology with an Agile approach to design and implement the AMLE framework. The proposed architecture operates across three distinct layers: device, network, and cloud. At the device layer, lightweight encryption algorithms were implemented to accommodate resource limitations. The network layer incorporated anomaly detection mechanisms using machine learning techniques to identify suspicious traffic patterns. The cloud layer implemented Attribute-Based Access Control (ABAC) to manage authentication, authorization and encryption for data storage. Testing was conducted in a controlled environment that simulated typical smart home conditions, with evaluation focused on functional correctness, integration capabilities, performance impact, and security effectiveness. Findings demonstrate that the AMLE model effectively enhances protection against unauthorized access attempts, botnet infiltration, and data exfiltration while maintaining acceptable performance levels on resource-constrained devices. The adaptive capabilities of the system enable real-time security adjustments based on detected threat levels, device capabilities, and data sensitivity. This research contributes to the field of IoT security by providing a practical encryption framework that balances security requirements with the operational constraints of smart home environments.

Keywords: Smart Home Security, IoT Encryption, Adaptive Security, Multi-Layer Protection, Resource-Constrained Devices, Privacy Preservation