An Ai-orchestrated Multi-factor Authentication System Based on Behavioral Biometrics in Cloud Applications
Year: 2025
Type: article
Abstract: The growing reliance on applications that are hosted on the cloud has made traditional authentication techniques, especially the use of passwords and one-time passcodes, inadequate to counter the advanced cyber-attacks.This paper proposes a multi-factor authentication (MFA) architecture with an algorithm-based approach that uses behavioral biometrics including typing rhythm, mouse dynamics and touchscreen gestures as a passive, continuous form of user corroboration.The behavioral traits are by nature non-replicable, thus allowing the system to identify anomalies in real-time.Machine-learning methods build dynamic user profiles and are able to dynamically adjust to behavioral drift without compromising usability.The framework combines behavioral biometrics with contextual data like geolocation and device fingerprinting to provide adaptive security that adapts to the risk profile of each session.This hybrid MFA model enhances security without creating too much friction to legitimate users, which makes it even more applicable to sensitive cloud environments, such as healthcare, banking, and enterprise-level SaaS platforms.Evaluations of experimental results show a high accuracy of separating genuine and impersonated Omkar Reddy Polu https://iaeme.com/Home/journal/IJAIRD 60 editor
Author: Omkar Reddy Polu
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W4413328158