Enhancing Cloud Security: A Multi-Factor Authentication and Adaptive Cryptography Approach Using Machine Learning Techniques

Storing files, photos, bank records and office work on the internet ("the cloud") is now a part of everyday life in India and across the world. This convenience also brings a danger: if a stranger gets into someone's cloud account, that person's private data can be stolen or misused. This paper explains, in simple words, a security design that protects cloud data in two ways. First, it checks who is logging in using several proofs together (password and PIN, fingerprint or face, a one-time code, and the way the person normally behaves). Second, it protects the data itself with locks that can change automatically when danger is sensed. A learning program (machine learning) watches every login, gives it a risk score, and decides whether to allow it, ask for more proof, or block it. The paper walks through each block of the architecture, explains how the blocks work together using a day to-day example, compares the design with the usual "password only" method, shows the screens of a working prototype called CloudShieldAI, and discusses limits, privacy and future work. The aim is that even a reader without a technical background can look at the architecture diagram and understand how it keeps cloud data safe