Exploring Audio Editing Features as User-Centric Privacy Defenses Against Large Language Model(LLM) Based Emotion Inference Attacks Article Swipe

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Mohd. Farhan Israk Soumik , W.K.M Mithsara , Abdur R. Shahid , Ahmed Imteaj ·

YOU? · · 2025 · Open Access · · DOI: https://doi.org/10.48550/arxiv.2501.18727

The rapid proliferation of speech-enabled technologies, including virtual assistants, video conferencing platforms, and wearable devices, has raised significant privacy concerns, particularly regarding the inference of sensitive emotional information from audio data. Existing privacy-preserving methods often compromise usability and security, limiting their adoption in practical scenarios. This paper introduces a novel, user-centric approach that leverages familiar audio editing techniques, specifically pitch and tempo manipulation, to protect emotional privacy without sacrificing usability. By analyzing popular audio editing applications on Android and iOS platforms, we identified these features as both widely available and usable. We rigorously evaluated their effectiveness against a threat model, considering adversarial attacks from diverse sources, including Deep Neural Networks (DNNs), Large Language Models (LLMs), and and reversibility testing. Our experiments, conducted on three distinct datasets, demonstrate that pitch and tempo manipulation effectively obfuscates emotional data. Additionally, we explore the design principles for lightweight, on-device implementation to ensure broad applicability across various devices and platforms.

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Type: preprint
Language: en
Landing Page: http://arxiv.org/abs/2501.18727
PDF: https://arxiv.org/pdf/2501.18727
OA Status: green
Related Works: 10
OpenAlex ID: https://openalex.org/W4407092942

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OpenAlex ID: https://openalex.org/W4407092942

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DOI: https://doi.org/10.48550/arxiv.2501.18727

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Title: Exploring Audio Editing Features as User-Centric Privacy Defenses Against Large Language Model(LLM) Based Emotion Inference Attacks

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Type: preprint

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Language: en

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Publication year: 2025

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Publication date: 2025-01-30

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Authors: Mohd. Farhan Israk Soumik, W.K.M Mithsara, Abdur R. Shahid, Ahmed Imteaj

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Landing page: https://arxiv.org/abs/2501.18727

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PDF URL: https://arxiv.org/pdf/2501.18727

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Concepts: Inference, Computer science, Internet privacy, Computer security, Human–computer interaction, World Wide Web, Artificial intelligence

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Cited by: 0

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Related works (count): 10

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