The use of Android devices has increased rapidly in recent years, increasing the chance of hacking and crime. Hackers target smartphones for various purposes, including getting sensitive information, financial fraud, identity theft, and other crimes. As a result, Android users must be aware of these possible dangers and take necessary measures to secure their smartphones. Because smartphones are the primary repository of personal sensitive information, smartphone designers must include security measures and encourage users to install freely available security software. Most studies have evaluated facial recognition as the most secure feature. This paper shows the uses of a facial recognition application to protect user files that contain sensitive information. The application uses machine-learning algorithms, specifically a Convolutional Neural Network (CNN) for face recognition that detects the user's face, tries to access the file, compares it with the basic image in the local file, and gives the result of whether to open the file or reject depending on the compared image. The application addresses critical concerns and improves file privacy features on Android devices, ensuring user file safety, and achieving success with 99% accuracy. It can also distinguish the faces of women wearing a shawl and people wearing glasses.