FDAE Lightweight Privacy Protection Based on Face Detection and Image Encryption

The"FDAE_Lightweight_Privacy_Protection_Based_on_Face_Detection_and_Image_Encryption" addresses the critical challenge of safeguarding sensitive data through advanced privacy protection mechanisms. In the age of digital transformation, the need for robust and efficient methods to ensure data privacy is growing, especially for sensitive personal information such as images and biometric data. This project proposes a novel privacy-preserving system that integrates face detection and image encryption techniques to offer a secure and efficient solution for protecting personal data. At the core of the system, the Advanced Encryption Standard (AES) algorithm is employed to encrypt images, ensuring that only authorized users can access and view the contents. AES, known for its efficiency and strength in providing symmetric encryption, serves as the backbone for securing image data during storage and transmission. This encryption ensures that even if the image files are intercepted or accessed without permission, the data remains unreadable, thereby protecting sensitive information such as user profiles, healthcare records, or financial data. Simultaneously, the Local Binary Pattern Histogram (LBPH) algorithm is utilized for face recognition. LBPH is a powerful face recognition technique that works by comparing the local patterns within an image and encoding these patterns as histograms. It is known for its robustness to variations in lighting and facial expressions, making it highly effective in real-world applications. LBPH allows the system to authenticate users based on their facial features, providing an additional layer of security through biometric verification. The integration of AES encryption and LBPH face recognition in this project offers several advantages. First, it provides a lightweight solution, making it ideal for resource-constrained environments where speed and efficiency are critical, such as in mobile applications or embedded systems. Secondly, the combination of image encryption and biometric authentication ensures a high level of security, minimizing the risk of unauthorized access while maintaining usability and performance.

Keywords:
Face Detection, Privacy Protection, Image Encryption, AES, LBPH, Data Security, Authentication, Lightweight, Face Recognition, Secure Systems, Biometric Authentication, Symmetric Encryption, Privacy Preservation.