Multi-Sensory Password System for Emergent Users
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Solution Overview
Problem
Conventional authentication mechanisms are inadequate for Basic Emergent Users (BEUs), as they struggle with generating strong, unique passwords due to limited literacy and cognitive abilities, leading to poor entropy and increased vulnerability to brute force attacks, especially when text-based entry mechanisms are cumbersome and prone to shoulder surfing and password reuse.
Innovation Solution
A method and system for recognition-based multi-skill-multi-sensory passwords that generate user profiles based on task-based techniques, grading user capabilities across sensory categories, and dynamically selecting input combinations from an entropy matching tree, offering a customized layout for password generation and authentication that splits entropy across multiple sensory inputs, reducing reliance on recall and enhancing usability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If Character Digit Symbol (CDS) passwords are used for authentication, then password security is improved, but usability and ease of generation deteriorate for Basic Emergent Users (BEUs)
Solution Approach 1:
The patent replaces text-based mechanical input mechanisms with voice-based acoustic input for password generation. BEUs can speak passwords naturally without navigating complex keyboards or menus, substituting the mechanical text entry process with speech recognition technology. This maintains strong password security while dramatically improving ease of generation for users with limited literacy.
2Reliability
If recall-based password entry mechanisms are used, then authentication security is improved, but usability deteriorates for users with memory limitations
Solution Approach 1:
The patent inverts the traditional recall-based authentication approach by implementing recognition-based authentication. Instead of requiring users to recall and type their password, the system presents multiple password options to the user and asks them to recognize and select their password. This maintains security by still requiring password knowledge while eliminating the memory burden of recall, making it accessible to users with memory limitations.
3Device complexity
If standard authentication mechanisms are provided for all users, then system simplicity is improved, but adaptability to different user capabilities deteriorates
Solution Approach 1:
The patent implements dynamic adaptability by detecting user type (BEU or non-BEU) and automatically adjusting the authentication interface and input methods accordingly. The system transitions from a static, one-size-fits-all approach to a dynamic system that adapts its complexity and interaction mode based on real-time user capability assessment, providing simplified voice-based interfaces for BEUs while maintaining standard options for other users.
4Object-affected harmful factors
If password entropy is increased for security, then resistance to brute force attacks is improved, but difficulty of password generation increases for BEUs
Solution Approach 1:
The patent enables BEUs to generate high-entropy passwords independently through natural speech without requiring assistance from others or complex system guidance. The voice-based system captures the full entropy of the user's spoken password, allowing BEUs to create strong, unique passwords on their own, eliminating the need for password managers or assistance while maintaining high security standards.
Data Source
AI summary
State of the art authentication mechanisms have limitations when used by Basic Emergent User (BEU). Embodiments herein provide method and system for recognition based multi-skill-multi-sensory passwords with dynamic identification of sensor combination based on end user skill, specifically for the BEU. The method disclosed generates user profile using a task-based technique to determine skill and capability of the user associated with each of a plurality of sensory categories used for generating a multi-skill-multi-sensory password. Each of the plurality of sensory categories are graded is descending order based on user's skill and capability and user is offered to select each password entry from a particular sensor category in accordance with the identified grade in each iteration. Thus, the entropy of password generation in the context of user is split among the sensor categories. Furthermore, recognition-based out of sequence approach is used during user authentication instead of more challenging memorizing-based approach.