Acoustic Scene Classification for Secure Automated Voice Calls
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Solution Overview
Problem
Existing automated voice-based systems lack context-awareness, making them vulnerable to malicious attacks such as impersonation and eavesdropping, particularly in public environments where sensitive information may be compromised.
Innovation Solution
A computer-implemented method using acoustic scene classification to identify user environments during voice calls, comparing them to a preconfigured whitelist, and performing security policy actions such as forwarding calls to humans or requiring multi-factor authentication when the environment is not approved.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated voice-based systems are used to handle telephone interactions, then productivity and automation extent are improved, but security and reliability deteriorate due to vulnerability to malicious attacks
Solution Approach 1:
The patent introduces an acoustic scene classification system as an intermediary between the automated voice-based system and the user environment. This mediator analyzes acoustic signals to classify the environment (e.g., private vs. public spaces) and provides context information to the automated system, enabling security decisions without human intervention while maintaining automation productivity
Solution Approach 2:
The system performs preliminary acoustic scene classification before processing sensitive information during voice interactions. By classifying the environment in advance, the system can proactively apply security policies (such as preventing information disclosure in public spaces) before malicious attacks or security breaches occur, rather than reacting after the fact
2Reliability
If context-awareness is added to automated systems to improve security, then reliability is improved, but device complexity increases
Solution Approach 1:
The patent replaces complex mechanical or manual security verification systems with acoustic scene classification. Instead of requiring multiple authentication factors or human agents to assess environment context, the system uses acoustic signal processing to automatically classify environments, reducing operational complexity while maintaining security reliability
Solution Approach 2:
The system changes the parameter used for security decisions from traditional authentication data to acoustic environment parameters. By classifying environments based on acoustic characteristics (noise levels, reverberation, ambient sounds), the system adds context-awareness using a different parameter space that doesn't significantly increase system complexity
3Reliability
If acoustic scene classification is implemented to identify user environments, then security is improved, but loss of time increases due to additional processing steps
Solution Approach 1:
The system performs acoustic scene classification periodically or at key moments during voice interactions rather than continuously. This periodic analysis occurs at natural breakpoints in the conversation or when security-relevant events are detected, providing necessary security context while minimizing time loss compared to continuous monitoring
Solution Approach 2:
The acoustic scene classification is performed rapidly using efficient signal processing algorithms that can quickly analyze acoustic parameters and classify environments. The system rushes through the classification process during brief intervals in the conversation, minimizing the time added to each interaction while still providing security benefits
Data Source
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AI summary
According to an embodiment, a computer-implemented method for call security comprises: receiving a call from a user; identifying an environment of the user during the call using acoustic scene classification; comparing the identified environment to a preconfigured environment whitelist; and in response to at least the preconfigured environment whitelist not comprising the identified environment, performing at least one security policy action.