Savka M. Energy-aware adaptive management of cryptographic security in IoT Fog nodes

The dissertation research is devoted to increasing the hardware survivability and energy efficiency of electronic systems in mobile IoT Fog nodes operating under autonomous power supply. The aim of the work is to develop a method for adaptive management of processor load (caused by cryptographic protection) based on fuzzy logic. The object of the research encompasses the processes of energy consumption and computing resource management to ensure physical survivability in hardware nodes of Fog Computing, while the subject includes the corresponding methods and models of adaptive management. The study employs methods of system analysis, fuzzy logic, and hardware-software modeling. The scientific novelty of the research lies in the development of an adaptive energy-aware method for managing cryptographic load, which dynamically coordinates the choice of a cryptographic primitive with the current energy reserve to counter battery exhaustion attacks. Furthermore, the concept of hardware survivability for microprocessor systems is advanced through the deliberate reduction of computing load in critical energy modes. The use of an integral quality criterion to formalize the trade-off between latency, energy consumption, and computing capabilities is substantiated for the first time, and the modeling methodology for verifying ARM-based systems is improved. The practical significance of the obtained results lies in the ability to extend the autonomous operation time of a Fog node under network load by 1.7 times. These findings form the basis for designing embedded IoT devices, developing attack-resistant industrial gateways, and creating firmware for smart power controllers.