Cognitive User Identification Recommendation via Typing Pattern Analysis
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Solution Overview
Problem
Users often resort to easy-to-remember but less secure passwords due to difficulties in remembering randomly generated secure passwords, leading to potential security breaches, as they either choose insecure alternatives or store generated passwords in unsafe locations.
Innovation Solution
A method and system that monitor and analyze typing patterns across various applications and devices to generate personalized, memorable password recommendations based on user behavior, utilizing data structures and machine learning to suggest passwords consistent with application and device types.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If programs automatically generate secure passwords, then password security is improved, but user memorability deteriorates
Solution Approach 1:
The system performs preliminary analysis of user typing patterns and behavioral characteristics before password generation. By pre-processing user input data across multiple applications and devices, the system builds a behavioral profile that informs subsequent password creation, ensuring both security and memorability from the outset
Solution Approach 2:
The system continuously monitors and analyzes user typing patterns as feedback to refine password recommendations. By tracking how users actually type across different applications and devices, the system adjusts generated passwords to better match user behavior patterns, improving both security and ease of recall
2Ease of operation
If users choose easy-to-remember passwords, then user memorability is improved, but password security deteriorates
Solution Approach 1:
The system enables users to create their own secure passwords by analyzing their natural typing patterns. Users inadvertently provide the raw material for secure password generation through their own input behavior, eliminating the need to choose between security and memorability
Solution Approach 2:
The system transforms user typing parameters (speed, rhythm, repetition patterns) into password characteristics. By changing the parameters of password generation from random character selection to behavior-based pattern encoding, the system creates passwords that are both secure and naturally memorable to each user
3Adaptability or versatility
If the system monitors typing patterns across multiple applications and devices, then password personalization is improved, but system complexity increases
Solution Approach 1:
The system implements a universal behavioral analysis engine that operates across multiple applications and device types. By creating a single, multi-functional monitoring and analysis system that handles diverse input sources through unified processing logic, the system achieves high personalization without proportionally increasing complexity
Solution Approach 2:
The system segments the password generation process into distinct modules: typing pattern monitoring, behavioral analysis, data structure generation, and password recommendation. This segmentation allows each component to be optimized independently while working together to provide personalized passwords across multiple applications and devices
Data Source
AI summary
Embodiments of the present invention provide a method, system and computer program product for cognitive user identification recommendation. In an embodiment of the invention, a method for cognitive user identification recommendation includes monitoring typing patterns of an end user as the end user enters data in different fields of different applications of a computing device having a device type and categorizing each of the fields and applications according to field type and application type. The method further includes generating a data structure mapping the user typing patterns to each type of field and application to model user input behavior of the end user. The method also includes transmitting the data structure to a requesting application for prompting the end user to provide a particular type of password mapped to the modeled user input and consistent with a field type of the password and a type of requesting application.