Wireless Eavesdropping Detection for Speech Confidentiality

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Solution Overview

Problem

In open-plan workspaces, eavesdropping poses a significant threat to confidential information due to reflective building materials, and conventional soundproofing solutions are costly and require physical modifications.

Innovation Solution

Utilizing wireless signal strength and triangulation to estimate building materials and sound attenuation, employing machine learning to improve eavesdropping detection, and activating eavesdropping countermeasures when potential overhearing is detected.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Loss of information

If conventional soundproofing solutions are used, then speech confidentiality is improved, but cost and device complexity increase significantly

Engineering Contradiction:

Improvespeech confidentialityVSAvoidphysical modifications

Core Design Contradiction:

Loss of informationVSDevice complexity

Solution Approach 1:

The patent replaces physical soundproofing structures with an electronic system that uses wireless signal analysis, machine learning models, and software-based eavesdropping detection to achieve speech confidentiality protection without requiring physical modifications to the environment

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The patent introduces wireless access points and signal analysis systems as intermediaries to detect and prevent eavesdropping, using wireless signals as a proxy to infer acoustic environment properties and identify potential eavesdropping risks without direct acoustic measurement

Inventive Principle:

Principle #24Intermediary (Mediator)

2Ease of operation

If wireless signal analysis is used to estimate sound attenuation, then ease of operation is improved, but measurement precision may be affected

Engineering Contradiction:

Improveeavesdropping detectionVSAvoidsound attenuation estimation

Core Design Contradiction:

Ease of operationVSMeasurement precision

Solution Approach 1:

The patent employs machine learning models that are iteratively trained and improved using feedback from collected wireless signal data and actual eavesdropping detection outcomes, continuously refining the accuracy of sound attenuation estimates while maintaining ease of operation

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The patent changes the measurement parameter from direct acoustic measurement to wireless signal analysis, using the correlation between wireless signal propagation and sound attenuation to enable easy operation while compensating for precision limitations through environmental factor analysis and machine learning

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS12556927B2Speech confidentiality monitoring and alerting

Publication Date: 2026.02.17 CISCO TECHNOLOGY INC

AI summary

A method, computer system, and computer program product are provided for performing automated eavesdropping detection and remediation. A distance between a first and second wireless client device is determined with reference to a wireless access point based on wireless signals transmitted by the devices. A first and second signal loss are determined with reference to the first and second wireless client devices and the wireless access point. Material properties for any physical structures between the first and second wireless client devices are derived based on the signal losses. A sound attenuation is determined between the first and second wireless client devices based on the material properties. It is determined whether a first user of the first wireless client device can hear audio of a second user of the second wireless client device based on the sound attenuation determined between the first wireless client device and the second wireless client device.