Artificial Intelligence-Based Graphical Password Authentication for Enhanced Security

Author(s)	Ms. JINAL DIVYESHKUMAR PATEL, Dr. PAPRI DAS
Country	India
Abstract	Graphical password authentication offers a usable alternative to text passwords but remains vulnerable to shoulder surfing, brute-force, and guessing attacks due to static verification. This research proposes an AI-based graphical password framework that integrates image-based authentication with behavioural analysis. The system captures user interaction features such as mouse movements, click timing, cursor trajectory and interaction sequence to build a behavioural profile using machine learning models. During login, real-time behaviour is compared with the stored profile for adaptive, risk-based authentication, strengthening verification when anomalies are detected. The framework enhances resistance against common attacks while maintaining usability. Evaluation is based on security, accuracy, FAR, FRR and performance, demonstrating a more secure, adaptive and intelligent authentication approach.
Keywords	Artificial Intelligence, Graphical Password Authentication, Behavioural Analysis, Adaptive Authentication, Risk-Based Authentication, User Authentication, Authentication Security, Anomaly Detection, Password Attacks.
Field	Computer Applications
Published In	Volume 7, Issue 5, September-October 2026
Published On	2026-10-07

About AIJFR Fees & Payment Current Issue Publication Archive	Submit Research Paper Track Submission Status Publication Guidelines Publication Ethics Peer Review & Plagiarism	Join as a Reviewer Editors & Reviewers Reviewer Referral Program Get Reviewer Membership Certi.	Website/Journal Policies Usage Policy Content Policies Privacy Policy

Contact Us		+91-9898-79-39-59	editor@aijfr.com

Advanced International Journal for Research