Wireless Coverage Vulnerability Filtering Using Weak Fingerprints
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Solution Overview
Problem
Existing wireless network coverage vulnerability detection methods suffer from inaccuracies due to misjudgments caused by tidal phenomena and edge access points, leading to false positives in identifying coverage vulnerabilities.
Innovation Solution
A method that involves obtaining weak fingerprint data from terminals within a coverage area, determining suspected coverage vulnerabilities, and applying filter-out conditions based on time and space dimensions to differentiate between actual vulnerabilities and misjudgments, using clustering and edge AP identification to enhance accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If coverage vulnerability detection is performed using signal strength data, then coverage vulnerabilities can be identified, but false positives occur due to misjudgments from tidal phenomena and edge access points
Solution Approach 1:
The patent segments the detection process into multiple independent judgment dimensions: time dimension (checking if vulnerability appears in multiple acquisition cycles), space dimension (checking if it occurs in multiple locations), and access point dimension (identifying edge APs). This segmentation allows the system to distinguish between real coverage vulnerabilities and false positives by requiring evidence across multiple dimensions, thereby reducing false positives while maintaining detection accuracy.
Solution Approach 2:
The patent introduces new judgment dimensions beyond simple signal strength measurement. It adds temporal dimension (acquisition cycle frequency), spatial dimension (geographical distribution), and network topology dimension (edge AP identification). By transforming the one-dimensional signal strength check into a multi-dimensional assessment framework, the system effectively filters out false positives caused by tidal phenomena and edge effects while preserving true coverage vulnerability detections.
2Measurement precision
If multiple acquisition cycles are checked to improve accuracy, then false positives are reduced, but detection time increases
Solution Approach 1:
The patent applies partial action by checking a limited number of acquisition cycles (at least two) rather than continuously monitoring indefinitely. It also uses partial judgment by evaluating only specific criteria (time range, space distribution, edge AP status) rather than analyzing all possible parameters. This partial action approach reduces detection time while maintaining sufficient accuracy to filter false positives.
Solution Approach 2:
The patent performs preliminary identification of edge access points and pre-establishes judgment criteria before actual vulnerability detection. By pre-classifying APs as edge or non-edge based on network topology, and pre-defining the multi-dimensional judgment framework, the system reduces computation time during actual detection cycles. This preliminary preparation allows faster multi-dimensional assessment without sacrificing accuracy.
Data Source
AI summary
This application provides a wireless network coverage vulnerability processing method and apparatus, and a computing device. The method includes: obtaining weak fingerprint data, acquired by a wireless access point AP within a preset time period, of a terminal within a coverage area, where the weak fingerprint data of the terminal is signal data of the AP that is acquired by the terminal in the case of a weak signal; determining a suspected coverage vulnerability based on weak fingerprint data of each terminal; determining, based on the suspected coverage vulnerability, whether the suspected coverage vulnerability meets a filter-out condition; and when the suspected coverage vulnerability meets the filter-out condition, determining that the suspected coverage vulnerability is not a wireless network coverage vulnerability.