How to find a GSMem malicious activity via an AI approach

TL;DR

This paper presents an AI-based method for detecting GSMem malicious activity by analyzing electromagnetic wave data, demonstrating promising results with low false positive and negative rates.

Contribution

The paper introduces a novel AI approach utilizing electromagnetic data to effectively identify GSMem malicious activity, improving detection accuracy.

Findings

Low false positive rates achieved

Low false negative rates achieved

Effective detection of GSMem activity in simulations

Abstract

This paper investigates the following problem: how to find a GSMem malicious activity effectively. To this end, this paper puts forward a new method based on Artificial Intelligence (AI). At first, we use a large quantity of data in terms of frequencies and amplitudes of some electromagnetic waves to train our models. And then, we input a given frequency and amplitude into the obtained models, predicting that whether a GSMem malicious activity occurs or not. The simulated experiments show that the new method is potential to detect a GSMem one, with low False Positive Rates (FPR) and low False Negative Rates (FNR).