Determine electronic devices vulnerabilities using artificial intelligence

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 eavesdrop...

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Bibliographic Details
Main Authors: Vizitiu, Alexandru-Madalin, Dobrescu, Lidia, Molder, Cristian, Sebacher, Bogdan, Trip, Bogdan Catalin, Butnariu, Vlad Florian
Format: Conference Proceeding
Language:English
Subjects:
Artificial intelligence
audio
communications security
Eavesdropping
Electromagnetics
Machine learning algorithms
Security
TEMPEST
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Summary: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.
ISSN:1938-1883
DOI:10.1109/COMM62355.2024.10741490