SECURING CLOUD SYSTEMS WITH SMART AUTHENTICATION AND ADAPTIVE ENCRYPTION

Abstract

The necessity for sophisticated security measures to safeguard private information on distant servers is highlighted by the cloud computing industry's explosive growth. To protect these data, authentication is essential. Vulnerabilities continue despite the different approaches that have been suggested. Using data mining approaches based on an intrusion-detection system, this research presents a revolutionary multi-factor authentication system coupled with a hybrid cryptographic framework that dynamically changes encryption algorithms. The proposed system employs passwords, conditional attributes, and fingerprint authentication to derive the encryption key from fingerprint data. It uses a dual-encryption strategy that combines five algorithm pairs: AES + HMAC (SHA-256), ECC + HMAC (SHA512), HMAC-MD5 + PBKDF2, Twofish + Argon2, and Blowfish + HMAC SHA3-256. In order to secure the data, a hybrid model dynamically modifies an encryption algorithm to anticipate and categorize threats. Strong resistance to brute force, spoofing, phishing, guessing, and impersonation attacks was demonstrated by the framework. By putting this paradigm into practice in a cloud authentication environment, data confidentiality is greatly improved and unwanted access is prevented. This study demonstrates how multi-factor authentication and adaptive cryptography may be combined to create strong cloud security solutions.