Wireless Sniffer WLAN Traffic Identification with BSSID and SSID Matching
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Solution Overview
Problem
Existing wireless sniffers capture packets from multiple WLANs indiscriminately, leading to privacy concerns and inefficiencies, as they lack the ability to automatically distinguish between targeted and neighboring wireless networks without manual configuration.
Innovation Solution
A wireless sniffer employs a similarity metric to compare base station identities (BSSIDs) and service set identities (SSIDs) using a fixed connection to a network, allowing it to classify packets as belonging to the targeted or neighboring networks, and anonymize or drop neighboring packets accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If a wireless sniffer captures all packets on radio channels, then complete wireless traffic data is obtained, but packets from multiple WLANs are captured causing privacy issues and data overload
Solution Approach 1:
The patent segments wireless traffic into targeted WLAN packets and neighboring WLAN packets using similarity metrics. By dividing the captured traffic stream into distinct categories based on BSSID and SSID similarity comparisons, the system can process and handle different packet types differently, allowing complete capture while preventing privacy violations through selective anonymization of neighboring network packets.
Solution Approach 2:
The patent applies different quality treatments to different portions of captured traffic. Targeted WLAN packets receive full analysis and processing, while neighboring WLAN packets are anonymized by removing identifying information such as MAC addresses and SSIDs. This local differentiation ensures privacy compliance while maintaining analytical value.
2Measurement precision
If manual configuration is used to identify targeted WLAN packets, then accurate network identification is achieved, but device complexity and setup time increase
Solution Approach 1:
The patent implements self-service automation where the sniffer automatically identifies targeted WLAN packets without manual configuration. The system performs autonomous similarity metric calculations between captured packets and known network identifiers, automatically classifying packets as belonging to the targeted WLAN or neighboring WLANs, thereby eliminating manual setup while maintaining high identification accuracy.
Solution Approach 2:
The patent transforms the identification problem from manual parameter matching to automated similarity metric computation. By changing from exact parameter matching (requiring manual configuration) to similarity-based classification using computed metrics between BSSIDs and SSIDs, the system achieves accurate automatic network identification without increasing device complexity.
3Loss of information
If all captured packets are analyzed in detail, then comprehensive network analysis is achieved, but processing time and computational resources increase
Solution Approach 1:
The patent segments captured packets into targeted and neighboring WLAN categories before analysis. By dividing the traffic stream early in the processing pipeline based on similarity metrics, the system can apply different analysis depths to different segments, performing comprehensive analysis only on targeted WLAN packets while applying lighter processing to neighboring packets.
Solution Approach 2:
The patent applies different quality levels of analysis to different packet types. Targeted WLAN packets receive full detailed analysis to maintain complete information, while neighboring WLAN packets receive anonymized processing that removes identifying information but retains basic traffic pattern data. This local differentiation maintains analysis completeness for relevant traffic while reducing overall processing time.
Data Source
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AI summary
A wireless sniffer (1) for analysing the channel quality of a Wireless Local Area Network (WLAN) identifies which of the wireless transmissions it detects over a wireless interface (19) are carried on the WLAN it is analysing by having a dedicated link (9) from a network management system controlling the WLAN under investigation, over which signature data such as a MAC ID associated with the WLAN is received and stored (14) for comparison (16) with signature data associated with the wireless transmissions it detects on the wireless interface (19) it can identify which of the received wireless transmissions are carried on the WLAN it is to analyse (17).