Multilingual AI-Driven Password Strength Estimation with Similarity-Based Detection
Nikitha M. Palaniappan, Ying He

TL;DR
This paper introduces a multilingual, AI-driven password strength estimator that leverages non-English datasets, AI-generated data, and similarity-based detection to improve accuracy and address language-specific password vulnerabilities.
Contribution
It presents a novel multilingual password strength meter incorporating AI-generated data and similarity matching, specifically tailored for Indian passwords, outperforming existing models.
Findings
AI-generated data enhances password strength estimation.
Similarity-based detection improves weak password classification.
The Indian-specific PSM achieves near-perfect accuracy with Jaro similarity.
Abstract
Considering the rise of cyberattacks incidents worldwide, the need to ensure stronger passwords is necessary. Developing a password strength meter (PSM) can help users create stronger passwords when creating an account on an online platform. This research aimed to explore whether incorporating a non-English training dataset (specifically Indian) can improve the performance of a PSM. Findings show that PSMs can be improved by utilising learning of words from other languages. Another contribution of the research was to compare and provide an analysis of AI generated data (specifically by ChatGPT) and PassGAN (existing state-of-the-art model), proving that PassGAN-like tools may no longer be needed as the performance is higher using AI generated data. To further strengthen detection, a Jaro similarity-based matching mechanism was incorporated, enabling the classification of passwords that…
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Taxonomy
TopicsUser Authentication and Security Systems · Emotion and Mood Recognition · AI in Service Interactions
