Deep Learning Weak Password Detection Model
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing weak password detection methods suffer from low accuracy rates due to the need for large weak password databases or feature extraction, which can lead to false detections and inefficiencies.
Innovation Solution
A weak password detection method and device based on deep learning, which involves acquiring a password character string, preprocessing it, and using a fully trained deep learning model to classify the password as strong or weak, thereby improving detection accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a weak password database is established for matching, then detection can be performed, but the detection speed is slow and false detections occur when the password is weak but not in the database
Solution Approach 1:
The patent replaces the mechanical database matching system with a deep learning-based neural network system. The neural network processes password characters through multiple layers (embedding layer, convolutional layers, pooling layers, fully connected layers) to classify passwords as weak or strong, eliminating the need for traditional database matching and achieving both high accuracy and fast detection speed
Solution Approach 2:
The patent changes the detection approach from binary database matching to multi-class classification using neural networks. The model learns complex patterns from training data and makes predictions based on learned representations, transforming the detection problem from simple string matching to sophisticated pattern recognition, thereby improving both accuracy and speed
2Reliability
If feature information extraction is used for detection, then detection can be performed, but the detection accuracy is limited by the model's ability to distinguish features
Solution Approach 1:
The patent replaces manual feature extraction with an automated deep learning system. The neural network automatically learns relevant features from raw password data through its layered architecture, eliminating the need for predefined feature extraction rules and improving detection accuracy without increasing operational complexity
Solution Approach 2:
The deep learning model performs self-learning during training, automatically identifying and extracting meaningful patterns from the training data. The model builds its own feature representations through convolutional and fully connected layers, eliminating the need for external feature engineering and simplifying the overall system
Data Source
AI summary
A weak password detection method and device based on deep learning, an electronic device, and a storage medium are provided. The method includes: acquiring a password character string to be detected; processing, by applying a fully trained weak password detection model, the password character string to be detected to obtain a strong/weak password classification label of the password character string to be detected, the fully trained weak password detection model being obtained by training a deep learning model with a password character string as an input and a strong/weak password classification label corresponding to the password character string as a supervision; and marking the password character string to be detected as a weak password under the condition that the strong/weak password classification label is a weak password label.