The field of secure data processing is moving towards the development of innovative solutions that enable secure and efficient processing of sensitive data. Recent advancements have focused on leveraging homomorphic encryption and other cryptographic techniques to protect user privacy in various applications, including face recognition, recommendation systems, and image encryption. These solutions aim to address the significant privacy risks associated with unauthorized access to sensitive biometric data and other personal information. Notable papers in this area include: CryptoFace, which introduces an end-to-end encrypted face recognition system with fully homomorphic encryption, and Efficient Privacy-Preserving Recommendation, which proposes a novel approach combining Compressed Sparse Row representation with FHE-based matrix factorization for efficient recommendation systems. Additionally, the Image Encryption Scheme Based on Hyper-Chaotic Map and Self-Adaptive Diffusion presents an innovative image encryption scheme that integrates a novel 2D hyper-chaotic map with a self-adaptive diffusion method, demonstrating superior performance compared to existing state-of-the-art image encryption techniques.