Security Prejudgment Using Characteristic Information and Bayes Theorem
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Solution Overview
Problem
Conventional monitoring systems fail to identify potential risks not reflected in spatial information, leading to safety hazards and inefficient data transmission during prolonged monitoring processes.
Innovation Solution
A method and device for security prejudgment based on characteristic information, using Bayes' theorem to calculate security status from received data, transmitting login keys or prompt messages to manage risk assessment and optimize data intervals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If preset dangerous conditions are monitored in existing systems, then specific security risks can be detected, but potential risks not covered by preset conditions cannot be identified
Solution Approach 1:
The system performs preliminary security assessment by analyzing characteristic information before dangerous conditions actually occur. It calculates security status information based on multiple characteristics (location, time, behavior patterns) to predict potential risks in advance, enabling proactive rather than reactive monitoring.
Solution Approach 2:
The patent transitions from traditional spatial-based monitoring to multi-dimensional characteristic analysis. Instead of only monitoring preset geographic boundaries, the system analyzes multiple dimensions including temporal patterns, behavioral characteristics, and contextual information to identify risks that cannot be detected by spatial information alone.
2Reliability
If continuous monitoring is performed via wireless communications, then real-time security status can be obtained, but data traffic is wasted during prolonged monitoring processes
Solution Approach 1:
The system implements periodic monitoring with dynamically adjusted intervals based on security risk levels. When security status is normal, monitoring frequency is reduced to save traffic. When risk levels increase, the system automatically increases monitoring frequency, achieving adaptive periodic action that balances real-time detection with resource conservation.
Solution Approach 2:
The system uses feedback mechanisms where security status information calculated from characteristic data feeds back into adjusting future monitoring strategies. Based on the calculated security status and risk assessment, the system dynamically adjusts monitoring intensity and data transmission frequency, creating a closed-loop control that optimizes traffic usage while maintaining security.
Data Source
AI summary
An example method of security prejudgment based on characteristic information include receiving characteristic information of a monitored party from the monitored party, calculating security status information of the monitored party based on a probability of danger that has been stored and corresponds to the characteristic information of the monitored party, determining that the security status information is greater than a first threshold, performing an appropriate operation based on the determination. Accordingly, the technical solution of the present disclosure solves a problem that presetting of monitoring conditions cannot cover potential surrounding risks that result in a safety hazard. Further, the technical solution can monitor risks that are not reflected by spatial information. After identifying and warning based on the characteristic information, potential risks may be avoided before occurring without wasting data traffic.