Cloud Continuous Multifactor Authentication via Sensor Challenges
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Solution Overview
Problem
Current multifactor authentication methods are inadequate in ensuring continuous and secure user authentication, particularly when the trust score of a user device falls below a certain threshold, as they lack a secure and convenient way to re-authenticate users and are vulnerable to attacks when the device is compromised.
Innovation Solution
A cloud-based continuous multifactor authentication system that utilizes a combination of sensors and a neural network to continuously monitor and re-authenticate users by sending challenges based on trait data, such as biometric and contextual information, to ensure secure access to devices, even when the initial trust score is below a threshold.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional single-factor or two-factor authentication is used, then ease of operation is improved, but reliability deteriorates as attackers increasingly compromise user devices
Solution Approach 1:
The system continuously monitors device trust scores and authentication factors, providing feedback loops that dynamically adjust security measures. Sensors continuously collect trait data and update authentication status, creating a real-time feedback mechanism that maintains security while allowing convenient access for legitimate users.
Solution Approach 2:
The authentication system transitions from static single-factor or two-factor authentication to dynamic continuous multifactor authentication. The system adapts authentication requirements based on real-time trust scores, device behavior, and sensor data, making security measures flexible and responsive to changing conditions.
2Reliability
If multifactor authentication is implemented, then reliability is improved, but device complexity increases and there is no secure convenient way to re-authenticate when trust score drops
Solution Approach 1:
The system automatically monitors trust scores and triggers re-authentication processes without requiring user intervention. When a device's trust score drops below thresholds, the system autonomously initiates challenge-response sequences using sensor data and neural networks to verify authenticity, reducing complexity for users while maintaining high security.
Solution Approach 2:
The system performs preliminary authentication checks continuously in the background using sensors and trait data before actual access is needed. By pre-establishing baseline trust scores and monitoring device behavior proactively, the system prepares authentication credentials and challenges in advance, reducing the complexity of on-demand re-authentication.
3Reliability
If continuous monitoring is implemented to maintain authentication, then reliability is improved, but use of energy increases
Solution Approach 1:
Instead of continuous high-power monitoring, the system uses periodic authentication challenges and trust score updates. Sensors collect trait data at intervals, and the neural network processes challenges periodically rather than continuously, reducing energy consumption while maintaining reliable authentication through strategic sampling and event-triggered updates.
Data Source
AI summary
Disclosed is an apparatus performing a method including: receiving, from an apparatus including a housing arranged to hold a personal communication device used by a user, a notification indicating a first authentication score of the user is below a first pre-determined threshold, providing a challenge to the personal communication device. In some embodiments, the challenge is selected based on one or more sensor data obtained by at least one of the apparatus or the personal communication device. In some embodiments, the method includes calculating a second authentication score based on a response to the challenge, and causing the apparatus, to gate electronic access to the personal communication device based on whether the second authentication score is above a second pre-determined threshold.