This study explores the use of artificial intelligence to detect and analyze electromagnetic emissions (EME) from monitors. By applying deep learning techniques, the proposed approach improves image reconstruction accuracy, helping to identify threats and reduce the risk of information leakage. Experimental results show significant improvements in detecting and restoring screen images from EME signals. The research also considers countermeasures and ways to minimize the risks associated with such attacks.