Network Activity Validation Using Smart Device Sensor Context
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Solution Overview
Problem
Current network security systems lack the ability to effectively differentiate between legitimate and fraudulent network activities, particularly when users are engaged in specific activities like sleeping, driving, or participating in sports, which can lead to unauthorized access or malicious activities.
Innovation Solution
A monitoring system that utilizes data from smart devices to determine the likelihood of user-initiated network activities, adjusting security settings and blocking suspicious activities by analyzing environmental and usage data, such as temperature, humidity, and motion sensors, to prevent unauthorized access.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If network security systems monitor all network activities, then security detection capability is improved, but false positives increase when users are engaged in activities like sleeping or driving
Solution Approach 1:
The patent introduces smart devices (wearables, mobile phones) as intermediary components that collect sensor data about user physical state and context. These devices act as mediators between the network security system and the user, providing additional information (motion, location, biometric data) that helps the security system accurately determine whether the user is capable of initiating network activities, thereby reducing false positives while maintaining detection precision
Solution Approach 2:
The system dynamically changes security validation parameters based on detected user state. When sensor data indicates the user is engaged in activities like sleeping, driving, or exercising, the system adjusts its validation thresholds and requirements. This allows the security system to maintain high detection precision for legitimate activities while reducing false positives during states when the user cannot reasonably initiate network actions
2Reliability
If the system blocks suspicious network activities, then network security is improved, but user convenience deteriorates due to potential blocking of legitimate activities
Solution Approach 1:
The system performs preliminary validation by analyzing sensor data before blocking network activities. By proactively assessing user state through smart device sensors (detecting if user is sleeping, driving, exercising), the system can preemptively allow or block activities based on likelihood of authorization. This preliminary assessment prevents unnecessary blocking of legitimate activities while maintaining security, thus preserving user convenience
Solution Approach 2:
The system implements feedback loops where sensor data continuously informs security decisions. The smart devices provide ongoing feedback about user physical state, and the security system adjusts its blocking behavior accordingly. This feedback mechanism ensures that legitimate activities are not mistakenly blocked while maintaining security posture, balancing reliability and ease of operation
3Measurement precision
If the system analyzes data from multiple smart devices, then accuracy of user activity detection is improved, but system complexity increases
Solution Approach 1:
The patent leverages the multi-functionality of smart devices that already contain various sensors for other purposes (fitness tracking, navigation, health monitoring). These devices perform multiple functions: their primary user-facing functions plus serving as security validation sensors. By reusing existing sensor infrastructure across multiple devices, the system achieves high detection accuracy without proportionally increasing system complexity, as the sensors serve dual purposes
Data Source
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AI summary
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for validating network activity. One of the methods includes receiving data identifying network activity for an online account; determining one or more users associated with the online account; determining, for each of the one or more users, a current physical activity in which the user is participating; determining, for each of the current physical activities, a likelihood that the corresponding user initiated the network activity while participating in the current physical activity; determining, for each of the current physical activities, whether the corresponding likelihood satisfies a threshold likelihood; and in response to determining that at least one of the corresponding likelihoods satisfies the threshold likelihood, providing an alert about the network activity to one of the one or more users associated with the online account.