SecureSpectra: Safeguarding Digital Identity from Deep Fake Threats via Intelligent Signatures
<|reference_start|>SecureSpectra: Safeguarding Digital Identity from Deep Fake Threats via Intelligent Signatures: Advancements in DeepFake (DF) audio models pose a significant threat to voice authentication systems, leading to unauthorized access and the spread of misinformation. We introduce a defense mechanism, SecureSpectra, addressing DF threats by embedding orthogonal, irreversible signatures within audio. SecureSpectra leverages the inability of DF models to replicate high-frequency content, which we empirically identify across diverse datasets and DF models. Integrating differential privacy into the pipeline protects signatures from reverse engineering and strikes a delicate balance between enhanced security and minimal performance compromises. Our evaluations on Mozilla Common Voice, LibriSpeech, and VoxCeleb datasets showcase SecureSpectra's superior performance, outperforming recent works by up to 71% in detection accuracy. We open-source SecureSpectra to benefit the research community.<|reference_end|>
@article{baser2024securespectra:,
    title={SecureSpectra: Safeguarding Digital Identity from Deep Fake Threats via
  Intelligent Signatures},
    author={Oguzhan Baser, Kaan Kale, Sandeep P. Chinchali},
    journal={arXiv preprint arXiv:2407.00913},
    year={2024},
    doi={10.21437/Interspeech.2024-2349},
    archivePrefix={arXiv},
    eprint={2407.00913},
    primaryClass={cs.CR cs.LG cs.SD eess.AS}
}