Dynamic Access Control Using Sensor Fusion and Machine Learning
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Solution Overview
Problem
Existing methods for securing electronic resources, such as password security and physical isolation, are inadequate in preventing unauthorized access, especially in remote work scenarios where direct physical control is challenging, and are labor-intensive and inefficient.
Innovation Solution
A system utilizing sensors to collect data on users and environments, combined with machine learning models to evaluate security levels and grant or block access, providing robust protection against unauthorized access and presentation attacks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If password security is used to protect electronic resources, then access control is provided, but it does not prevent access by unauthorized users who possess compromised passwords
Solution Approach 1:
The system transitions from static password authentication to dynamic multi-factor authentication that continuously evaluates multiple parameters including biometric data, device characteristics, location information, and behavioral patterns. This changes the security parameter from a single static factor to multiple dynamic factors that are constantly verified
Solution Approach 2:
The system introduces an intermediary access control system that sits between the user and the electronic resource. This intermediary continuously monitors and evaluates multiple authentication factors, acting as a mediator that can grant or deny access based on the combined assessment of various security parameters rather than relying solely on the password
2Reliability
If physical isolation and manual human oversight are used to secure electronic resources, then security is improved, but the system becomes expensive and labor intensive
Solution Approach 1:
The system implements self-service security monitoring through automated machine learning models that continuously analyze authentication data, device characteristics, and user behavior patterns. The system serves itself by automatically detecting anomalies and making access decisions without requiring constant manual human oversight, thereby reducing labor intensity while maintaining high security levels
Solution Approach 2:
The system incorporates continuous feedback loops where authentication outcomes, user behaviors, and system events are fed back into the machine learning models. This feedback mechanism allows the system to continuously improve its security assessments and adapt to new threats automatically, reducing the need for complex manual monitoring structures
3Reliability
If physical isolation is used to protect electronic resources, then security is improved, but access efficiency is reduced due to difficulty of access
Solution Approach 1:
The system replaces static physical isolation with dynamic virtual security boundaries that can adapt in real-time. Access controls are dynamically adjusted based on continuous evaluation of user credentials, device status, location, and behavior patterns, allowing legitimate access to flow smoothly while maintaining security without the rigidity of physical isolation
Solution Approach 2:
The system substitutes mechanical physical isolation mechanisms with electronic and software-based security controls. Instead of requiring physical presence in secure facilities or handling of physical media, the system uses digital authentication, encryption, and automated monitoring to provide equivalent or superior security with much higher access efficiency
Data Source
AI summary
A system for controlling access to an electronic resource can comprise a set of sensors and one or more processors. A first sensor in the set of sensors may detect first data indicating a characteristic of a user of the electronic resource. A second sensor in the set of sensors may detect second data indicating a characteristic of an environment of the electronic resource. The processors may use an ensemble of machine learning models to generate a score characterizing the user and characterizing the environment. The generated score may be evaluated based on one or more access criteria. Access to the electronic resource may be controlled based on the evaluation of the score.