AI based energy harvesting security methods: A survey
Masoumeh Mohammadi, Insoo Sohn
Abstract
Energy Harvesting (EH) as a power source plays a critical role in the advent of new technologies such as the Internet of Things (IoT). But, by providing power within the networks, it may be susceptible to attacks such as eavesdropping, data manipulation, or denial of service, leading to issues like leakage of confidential, sensitive information, and energy scarcity. Therefore, it is important to implement appropriate security measures to protect the data and devices that use energy harvested from ambient sources. In this paper, we present a comprehensive overview of the current and future developments of security for EH systems that used artificial intelligence(AI) approaches. Furthermore, we highlight the application of AI approaches such as machine learning (ML) and federated learning (FL) in the security of EH systems. Then, we discuss the security techniques that are used in the EH literature, including cryptography techniques, physical-layer security schemes, blockchain, and FL. Finally, we outline research challenges and prospects for developing and applying AI algorithms in the security of EH.