Treffer: A BRIEF STUDY ON MACHINE LEARNING, CRYPTOGRAPHY AND STEGANOGRAPHY

Cloud computing has become the foundation of progressive IT infrastructure, offering scalability, cost-efficiency, and flexibility. However, the unsealed and distributed nature of cloud system introduces abundant security threats, including data breaches, insider attacks, and denial-of-service attacks. Historic security mechanisms are often scarce to handle these dynamic threats. Machine Learning (ML), with its ability to discover anomalies and learn from data, offers prospective solutions for securing cloud platforms. Cryptography plays a critical role in preserving information in the online era. It provides the foundation for secure communication, authentication, and data integrity in various applications such as e-commerce, cloud computing, and blockchain. It also explores recent developments such as quantum-resistant cryptography, homomorphic encryption, and lightweight cryptography. Steganography, the art of hiding information within other seemingly safe data, has evolved significantly in recent years due to the proliferation of digital media. Unlike cryptography, which conceals the content of a message, steganography hides the presence of the message itself. It explores major applications such as digital watermarking, secure communication, and data integrity.