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Impersonation in the Digital Age: A Comparative Review of Detection Techniques Against Deepfakes
Subject area: Science,Engineering and Technology · Area of research: Impersonation
Abstract
Deepfakes?AI?generated or manipulated audio?visual content?pose a growing risk to identity verification, trust, and security. This comparative review synthesizes state?of?the?art detection techniques across visual, audio, and multimodal pipelines, focusing on performance, generalization, robustness, and operational considerations (latency, cost, and privacy). We analyze benchmark datasets (e.g., FaceForensics++, DFDC, FakeAVCeleb, WildDeepfake, ASVspoof 2021) and evaluation metrics (AUC, EER, F1) and compare classical, deep, and hybrid approaches. We also examine adversarial pressures?including compression, unseen manipulations, and cross?domain shifts?and outline practical integration patterns for KYC/AML, exam proctoring, and access control. The review concludes with an engineering blueprint for a multimodal detection stack, emphasizing human?in?the?loop triage and risk scoring.
Keywords
Deepfakes, Impersonation Detection, Multimodal Biometrics, Audio Spoofing, Media Forensics, Identity Verification, KYC, Liveness Detection, Robustness, Generalization
References
[1] Dolhansky, B., Bitton, J., Pflaum, B., Lu, J., Howes, R., Wang, M., & Canton Ferrer, C. (2020). The DeepFake Detection Challenge (DFDC) dataset. arXiv:2006.07397.
[2] Khalid, H., Woo, S., Choi, J., Shon, S., & Kim, J. (2021). FakeAVCeleb: A novel audio‑video multimodal deepfake dataset. NeurIPS Datasets and Benchmarks Proceedings.
[3] Rössler, A., Cozzolino, D., Verdoliva, L., Riess, C., Thies, J., & Nießner, M. (2019). FaceForensics++: Learning to detect manipulated facial images. Proceedings of ICCV.
[4] Yi, J., Wang, C., Tao, J., Zhang, X., Zhang, C. Y., & Zhao, Y. (2023). Audio deepfake detection: A survey. arXiv:2308.14970.
[5] Wang, X., et al. (2021). ASVspoof 2021: Accelerating progress in spoofed and deepfake speech detection. arXiv:2109.00537.
[6] Zi, B., Chang, M., Chen, J., Ma, X., & Jiang, Y.-G. (2021). WildDeepfake: A challenging real‑world dataset for deepfake detection. arXiv:2101.01456.
[7] Fu, X., Yan, Z., Yao, T., Chen, S., & Li, X. (2025). Exploring unbiased deepfake detection via token‑level shuffling and mixing. arXiv:2501.04376.
[8] Zhang, H., et al. (2025). A survey on multimedia‑enabled deepfake detection: State‑of‑the‑art, challenges, and future trends. Information Retrieval Journal (Springer).
[9] Al-Rubaye, W., et al. (2025). Audio‑visual multimodal deepfake detection leveraging emotional cues. International Journal of Advanced Computer Science and Applications, 16(6), — (details in paper).
How to cite this paper
@article{1710585,
author = {Ochi Victor Chukwudi, Tochukwu Chinecherem Nnabuike},
title = {Impersonation in the Digital Age: A Comparative Review of Detection Techniques Against Deepfakes},
journal = {Iconic Research And Engineering Journals},
year = {2025},
volume = {9},
number = {3},
pages = {648-651},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1710585.pdf},
abstract = {Deepfakes?AI?generated or manipulated audio?visual content?pose a growing risk to identity verification, trust, and security. This comparative review synthesizes state?of?the?art detection techniques across visual, audio, and multimodal pipelines, focusing on performance, generalization, robustness, and operational considerations (latency, cost, and privacy). We analyze benchmark datasets (e.g., FaceForensics++, DFDC, FakeAVCeleb, WildDeepfake, ASVspoof 2021) and evaluation metrics (AUC, EER, F1) and compare classical, deep, and hybrid approaches. We also examine adversarial pressures?including compression, unseen manipulations, and cross?domain shifts?and outline practical integration patterns for KYC/AML, exam proctoring, and access control. The review concludes with an engineering blueprint for a multimodal detection stack, emphasizing human?in?the?loop triage and risk scoring.},
keywords = {Deepfakes, Impersonation Detection, Multimodal Biometrics, Audio Spoofing, Media Forensics, Identity Verification, KYC, Liveness Detection, Robustness, Generalization},
month = {September},
}