Machine Learning-Based Solution for SMS Spam Detection Problem

The article describes a new method for image detection using machine learning, based on the development of sophisticated security systems tailored for examining digital media to identify and scrutinize altered images. Using deep learning models and advanced image processing techniques, the authors demonstrate high accuracy and efficiency i n detecting face modifications a nd malicious content within digital images. The authors illustrate the proposed technique by evaluating its performance on a unique dataset of unaltered and modified images. The method allows for improving detection accuracy by 93.99% and demonstrates robustness in real-time applications. The new method's effectiveness is confirmed by calculating precision and recall metrics. New research results develop advanced security solutions that can be used to enhance digital forensics, content authentication, and cybersecurity applications. Novelty and scientific contributions lie in integrating deep learning for real-time media analysis and enhancing data authenticity and integrity.