User-Centric Secure Service Provisioning with Sustainability in Resource Constrained Platforms Using Predictive Machine Learning Models

Abstract

This dissertation addresses the challenges of resource constraints and security vulnerabilities inherent in the increasing deployment of IoT devices and services. It embarks on a journey to optimize IoT service provisioning by recognizing the dynamic nature of user preferences and the need for robust security measures compatible with the limited computational, energy, and storage capacities of IoT devices. This foundational understanding leads to the initial contribution: a novel IoT simulation framework. This framework uniquely integrates lightweight cryptography - NtruEncrypt, within a user-centric service provisioning model, simulated using CupCarbon. The data collected from this framework validates the efficacy of lightweight security in enhancing Quality of Service (QoS) and also highlights the need for sophisticated resource management. Insights from the initial simulation inform subsequent works, driving the research towards comprehensive IoT optimization. Recognizing the urgency for improved resource management, the dissertation presents a two-phase IoT resource management optimization framework. This solution leverages predictive analytics of user service requests combined with a service recommendation methodology to dynamically reallocate IoT resources, thereby minimizing service delays and optimizing device efficiency. Focusing on sustained device operation, particularly in the context of emerging energy harvesting solutions, the work further develops an enhanced energy management framework. This framework dynamically optimizes the power distribution of harvested radio Frequency (RF) energy using a multi-objective optimization algorithm (NSGA-III) and a custom energy allocation algorithm, ensuring continuous service availability despite intermittent energy supplies. The final contribution is a secure energy scheduling framework for Energy Harvesting (EH)-enabled Sensor Cloud platforms. Directly countering energy depletion attacks by implementing dynamic, user-centric secure admission control, projecting each request’s net energy impact to block malicious requests before they can compromise the energy integrity of IoT devices. These contributions form a coherent and robust solution for dynamic, user-centric, and secure IoT service provisioning, resource management, and energy sustainability.