The Future of Cybersecurity: Innovations and Data Privacy Preserving Techniques

Abstract

The high increasing cybersecurity landscape has pushed the difficulties of providing strong security as well as respecting user privacy towards being an important concentration. This paper focuses on privacy-preserving techniques in the latest innovations of cybersecurity. This study contributes to analyze the prevalent methodologies today for instance homomorphic encryption, differential privacy and federated learning in order to strive not only a security secure but also private system using these state of art methodologies. The research goes on to describe the emerging trends and future direction in this area with some recommendations that could be used for writing secure protection of sensitive data across multiple applications