Anti-forensics of fake stereo audio using generative adversarial network

Author:

Liu Tianyun,Yan DiqunORCID,Yan Nan,Chen Gang

Funder

National Natural Science Foundation of China

Natural Science Foundation of Zhejiang Province

Natural Science Foundation of Ningbo

Ningbo Science and Technology Innovation 2025 Major Project

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Hardware and Architecture,Media Technology,Software

Reference30 articles.

1. Bao Y, Ruiyu L, Yun C et al (2016) Research progress on key technologies of audio forensics. J Data Acquis Process 31(2):252–259

2. Chen C, Zhao X, Stamm MC (2018) Mislgan: an anti-forensic camera model falsification framework using a generative adversarial network. 2018 25th IEEE International Conference on Image Processing (ICIP), pp 535-539. https://doi.org/10.1109/ICIP.2018.8451503

3. Chintala S, Denton E, Arjovsky M, Mathieu M (2017) How to train a GAN? Tips and tricks to make GANs work.[Online]. Available: https://github.com/soumith/ganhacks. Accessed 25 Jan 2021

4. Collobert R, Kavukcuoglu K, Farabet C (2011) Torch7: a matlab-like environment for machine learning AQ3. BigLearn NIPS Workshop

5. Diqun Y, Li X, Dong L, Wang R (2020) An Antiforensic method against AMR Compression Detection. Secur Commun Netw 2020, Article ID 8849902, 8 pp. https://doi.org/10.1155/2020/8849902

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2. Good or Evil: Generative Adversarial Networks in Digital Forensics;Advances in Information Security;2023-11-15

3. Audio Cross Verification Using Dual Alignment Likelihood Ratio Test;ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2023-06-04

4. Robust Anti-forensics on Audio Forensics System;Lecture Notes in Computer Science;2023

5. Training Scheme for Stereo Audio Generation;Communications in Computer and Information Science;2022

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