Determine electronic devices vulnerabilities using artificial intelligence
Alexandru-Mădălin Vizitiu, Lidia Dobrescu, Cristian Constantin Molder, Bogdan Sebacher, Bogdan Trip, Vlad Florian Butnariu · 2024
As electronic devices proliferate in both personal and professional settings, their susceptibility to electromagnetic vulnerabilities has become a critical concern. This article explores the use of artificial intelligence (AI) to identify and mitigate the risks associated with audio signal eavesdropping, a prevalent threat in the realm of electromagnetic security. By analyzing the electromagnetic emissions from electronic devices, AI techniques can detect unintended audio signal leaks that may compromise sensitive information. The study employs machine learning algorithms to process and evaluate these emissions. Results demonstrate the enhanced precision and efficiency of AI related to audio signal eavesdropping. This research not only underscores the importance of AI in fortifying the electromagnetic security of electronic devices but also paves the way for innovative approaches to safeguard against increasingly sophisticated eavesdropping techniques.