Dynamic User Authentication via Interaction Likelihood
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Solution Overview
Problem
Conventional user authentication techniques often face a trade-off between convenience and security, as they struggle to provide robust security measures without compromising user experience.
Innovation Solution
The system collects interaction data from user devices, compares it to profile information to determine a likelihood value of the current user's identity, and uses this value to adjust authentication processes, allowing for more intuitive and secure authentication methods.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional authentication techniques are used, then security can be provided, but user convenience deteriorates
Solution Approach 1:
The authentication system dynamically adjusts the required authentication strength based on the calculated likelihood value. When the likelihood value exceeds a threshold, minimal or no additional authentication is required, providing convenience. When the likelihood value is below the threshold, stronger authentication measures are applied, ensuring security. This dynamic adaptation resolves the contradiction between security and convenience.
Solution Approach 2:
The system changes the authentication parameter (likelihood value) based on real-time comparison of usage patterns and profile information. By adjusting the authentication requirement according to this parameter, the system achieves both security (when parameter indicates low likelihood) and convenience (when parameter indicates high likelihood), resolving the technical contradiction.
2Reliability
If robust security measures are implemented, then security is improved, but system complexity increases
Solution Approach 1:
The authentication system is segmented into multiple components: usage data collection, profile information storage, likelihood calculation, and conditional authentication enforcement. This segmentation allows the system to implement robust security measures only when necessary, rather than requiring complex authentication for all operations, thus improving security while managing system complexity.
Solution Approach 2:
The system automatically collects usage data, compares it with profile information, calculates likelihood values, and determines authentication requirements without user intervention. This self-service mechanism reduces the need for complex manual authentication processes while maintaining security, resolving the contradiction between security and system complexity.
Data Source
AI summary
Described herein are techniques for providing identification of a current user of a user device. Such techniques may comprise receiving a request for identification of a current user of a user device, receiving interaction data that includes information about current usage patterns for the user device, retrieving profile data associated with at least one potential user of the user device, comparing the profile data to the information about current usage patterns to determine for the at least one potential user of the user device, a likelihood value that the at least one potential user is the current user of the user device, and providing the determined likelihood value in response to the received request.