AI-Powered Data Encryption Techniques: Safeguarding Cloud Infrastructure

Although traditional encryption approaches remain essential for data protection, they fail to confront new generation threats and future problems created by quantum computers. As such, static protocols, little ability to evolve, and susceptibility to new attacks make them insufficient for protecting sensitive data in today's clouds. This paper presents AI -based encryption techniques as revolutionary solutions to these limitations. The main features are real-time dynamic key management, which relies on the generation, rotation, and distribution of keys in real time; behavior-based adaptive encryption, which adjusts chosen encryption parameters based on the user's activity and the system's behaviors; and AI -integrated lattice-based and hash-based quantum-resistant cryptographic algorithms. These innovations increase the ability of encryption speed and scalability, in addition to increasing resistance to complex and quantum-processing attacks. Several mathematical assessments and various examples from the real world show that the approach with the help of AI encryption algorithms is more effective than the traditional one within key parameters like security, time, and number of users. The study showcases the importance of employing AI within encryption, given that encryption could become necessary in data security in various sectors such as healthcare, finance, and government at the current growth trajectory. Adopting AI in encryption systems is now essential to provide strong data protection in an increasingly linked digital ecosystem as cyber threats become more complex.