Anomaly Detection Using Environmental Sensor Data
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Solution Overview
Problem
Conventional data security systems are inadequate in detecting usage anomalies in physical environments, as they rely on software-based traces and have high false-positive rates, especially in cases of insider attacks and compromised credentials.
Innovation Solution
A method that utilizes environmental sensor data, such as camera, door badge scanner, light sensor, and microphone data, to verify the presence of authorized users and detect usage anomalies by correlating user inputs with sensor data, preventing unauthorized access and reducing false positives through a weighting system and AI decision model.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If software-based authentication procedures are used, then access control is provided, but the system is vulnerable to forgery and insider attacks
Solution Approach 1:
The patent introduces environmental sensors (cameras, microphones, light sensors, door badge scanners) as intermediary devices that mediate between the user and the authentication system. These sensors capture physical environmental data (presence, location, time) to verify that authentication requests originate from authorized users in legitimate contexts, thereby preventing forgery and insider attacks without compromising authentication reliability
Solution Approach 2:
The patent replaces purely software-based authentication mechanisms with a hybrid system that incorporates physical environmental sensing. By substituting digital-only verification with physical presence detection through sensors, the system eliminates vulnerabilities to software-based forgery while maintaining authentication functionality
2Reliability
If software-based traces and UEBA are used for security monitoring, then IT security events can be tracked, but the false-positive rate is high and insider attacks are not effectively detected
Solution Approach 1:
The patent adds a new dimension to security monitoring by incorporating spatial and environmental data from physical sensors. Instead of relying solely on software event logs, the system now measures physical presence, location, and environmental context, creating a multi-dimensional verification framework that significantly reduces false positives and enables detection of insider attacks through physical behavior analysis
Solution Approach 2:
The environmental sensors automatically capture and provide verification data without requiring additional user action or manual intervention. The system self-verify authentication requests by correlating sensor data with authentication events, eliminating the need for complex manual verification processes and reducing false positives through automated environmental context analysis
3Reliability
If environmental sensors are integrated into the security system, then usage anomaly detection accuracy is improved, but system complexity increases
Solution Approach 1:
The patent employs multi-functional environmental sensors (cameras, microphones, light sensors, door badge scanners) that serve multiple purposes: authentication verification, presence detection, location tracking, and anomaly monitoring. This universal approach consolidates multiple security functions into single sensor devices, improving anomaly detection accuracy while minimizing the increase in system complexity through functional integration
Data Source
AI summary
Disclosed herein are systems and method for detecting usage anomalies based on environmental sensor data. A method may include: receiving a physical user input at a computing device located in an environment; determining whether the physical user input was received from an authorized user of the computing device by: retrieving environmental sensor data from at least one sensor located in the environment; identifying a window of time during which the physical user input was received; and verifying a presence of the authorized user at the environment during the window of time based on the environmental sensor data; and in response to determining that the authorized user was not present in the environment during the window of time, detecting a usage anomaly and not executing the physical user input.