VoIP Voice Quality Detection via Encrypted Wireless Traffic Analysis
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Solution Overview
Problem
In wireless local area networks operating under the IEEE 802.11 standard, it is challenging to determine the voice quality of VoIP calls due to encrypted wireless frames, which prevents the analysis of essential parameters like R-Value by examining the RTP fields.
Innovation Solution
A process is implemented to monitor and analyze wirelessly transmitted traffic between stations, determining the R-Value by calculating loss rate and burst rate based on missing frames and their arrival times, and using these metrics to assess voice quality despite frame encryption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If wireless frames are encrypted to secure VoIP data, then security is improved, but the ability to analyze RTP fields for voice quality measurement is lost
Solution Approach 1:
The patent introduces an intermediary approach by analyzing proxy packets and traffic patterns rather than directly examining encrypted RTP fields. The system uses the Access Point as an intermediary to monitor traffic characteristics (frame sizes, transmission intervals, bidirectional traffic balance) that indirectly reveal voice quality parameters without compromising the encryption security.
2Object-affected harmful factors
If frame encryption is applied to protect voice data, then data protection is improved, but the ability to determine R-Value by examining RTP fields is worsened
Solution Approach 1:
The patent extracts useful information from the encrypted traffic by focusing on metadata and traffic characteristics that are visible at the network layer. Specifically, it extracts frame size distributions, transmission timing patterns, and bidirectional traffic ratios from the encrypted wireless frames, which sufficient to calculate R-Value without extracting the actual encrypted voice data.
Solution Approach 2:
The system creates a copy of the traffic analysis approach by examining proxy packets and replicated traffic patterns. Instead of analyzing the original encrypted RTP streams directly, the system uses copies of traffic data (proxy packets, traffic matrices) that preserve the structural information needed for quality measurement while maintaining encryption integrity.
3Measurement precision
If traditional RTP field analysis is used for voice quality measurement, then measurement accuracy is improved, but compatibility with encrypted wireless frames is lost
Solution Approach 1:
The patent changes the measurement parameters from direct RTP field extraction to traffic pattern analysis. Instead of measuring voice quality through RTP timestamps and sequence numbers (which are inaccessible in encrypted frames), the system transforms the approach to measure quality through derived parameters like frame size distributions, transmission intervals, and traffic balance ratios, which remain accessible in encrypted wireless traffic.
Data Source
AI summary
In one exemplary embodiment, a process for detecting a phone includes monitoring wirelessly transmitted traffic between first and second stations. Next, the process determines whether the traffic sent in both directions between the first and second stations are close to each other in term of traffic volume. The process identifies a total frames count of a number of frames of an identical frame size transmitted, where the number of frames is greater than any number of frames of a same size. The process calculates the percentage of the count that was just collected out of the count of the total frames. The process identifies the first station as a phone if the calculated percentage is over a first threshold and the total frames count is over a second threshold.