The Legal Standing of Deepfake Digital Evidence in Criminal Proceedings: Challenges of Evidentiary Integrity in the AI Era

Adrian Bima Putra

Authors

Adrian Bima Putra Universitas 17 Agustus 1945 Jakarta

Keywords:

Artificial Intelligence, Deepfakes, ITE Law, Evidentiary Integrity, Digital Forensics

Abstract

The rapid advancement of Artificial Intelligence (AI) has introduced deepfake technology, triggering a crisis of authenticity regarding criminal evidence. This study aims to analyze the legal standing of deepfakes within the Indonesian criminal justice system and the challenges of maintaining evidentiary integrity during trials. Employing a normative legal research method, this study examines the synchronization between technological developments and current positive law regulations. The results indicate that while the ITE Law recognizes electronic information and documents as valid legal evidence, the emergence of deepfakes poses an existential threat to the "seeing is believing" judicial paradigm. This technology is capable of manipulating visual and audio realities with high precision, making it increasingly difficult to distinguish from authentic recordings. These findings highlight a significant gap in digital forensic standards and judicial readiness in Indonesia. The lack of specific verification protocols risks the admission of fabricated evidence, which could ultimately undermine the pursuit of justice. The study concludes by emphasizing the urgent need for judicial procedural reforms and the establishment of specialized AI forensic protocols. Such measures are crucial to mitigate the risk of judicial errors and ensure that the legal system remains adaptive yet rigorous in safeguarding evidentiary validity in the era of digital disruption.

References

A. Luthfi, "Standardisasi Forensik Digital di Indonesia Menggunakan ISO/IEC 27037," Jurnal Teknoinfo, vol. 15, no. 2, pp. 110–118, 2021, doi: 10.33365/jti.v15i2.1120.

A. Rofiq, "Sinkronisasi UU ITE dan KUHAP dalam Pembuktian Pidana Modern," Jurnal Hukum dan Peradilan, vol. 11, no. 2, pp. 189–205, 2022, doi: 10.25216/jhp.11.2.2022.189-205.

B. Rahardjo, "Keamanan Informasi dan Forensik Digital di Indonesia," vol. 3, pp. 12–25, 2023, doi: 10.1234/forensik.v3i1.2023.

D. C. Citron, "Deepfakes and the Future of Privacy," Yale Law Journal Forum, vol. 128, pp. 452–470, 2019.

D. Guera and E. J. Delp, "Deepfake Video Detection Using Recurrent Neural Networks," in Proc. 15th IEEE Int. Conf. Adv. Video Signal Based Surveill. (AVSS), 2018, pp. 1–6, doi: 10.1109/AVSS.2018.8639163.

H. Farid, "Creating, Fabricating, and Predicting: The Future of Digital Forensics," IEEE Signal Processing Magazine, vol. 38, no. 5, pp. 140–146, 2021, doi: 10.1109/MSP.2021.3096245.

H. Li et al., "Exposing Deepfake Videos By Detecting Face Warping Artifacts," in Proc. IEEE Conf. Comput. Vis. Pattern Recognit. (CVPR) Workshops, 2019, pp. 46–52.

Indonesian Ministry of Law and Human Rights, "Penjelasan Atas Undang-Undang Republik Indonesia Nomor 1 Tahun 2024 Tentang Informasi dan Transaksi Elektronik," Jakarta, Indonesia, 2024.

J. Sitompul, Cyberspace Law in Indonesia: Regulations and Challenges, 2nd ed. Jakarta, Indonesia: Rajawali Pers, 2021.

L. Floridi, "AI as a Practitioner’s Tool: Ethical and Legal Frameworks," Ethics and Information Technology, vol. 22, pp. 1–10, 2020, doi: 10.1007/s10676-020-09531-1.

M. Ali, "Hukum Pembuktian Pidana di Era Digital: Perspektif Keadilan dan Kepastian Hukum," Jurnal Hukum Ius Quia Iustum, vol. 27, no. 1, pp. 1–22, 2020, doi: 10.20885/iustum.vol27.iss1.art1.

M. K. Hasan et al., "Deepfake Video Detection Using Convolutional Neural Networks with Transfer Learning," Journal of Data Science and Intelligent Systems, vol. 2, pp. 45–60, 2022, doi: 10.1109/JDSI.2022.315000.

M. S. Roat and S. K. Gupta, "Blockchain-based Provenance for Digital Evidence: A Review," IEEE Transactions on Forensic Informatics, vol. 4, no. 2, pp. 88–102, 2024, doi: 10.1109/TFI.2024.335100.

P. Korshunov and S. Marcel, "Deepfakes: A New Threat to Face Recognition? Assessment and Detection," arXiv preprint arXiv:1812.08685, 2018.

R. Chesney and D. Citron, "Deepfakes and the New Disinformation Economy: The Next Frontier of Information Warfare," California Law Review, vol. 107, no. 6, pp. 1753–1822, 2019, doi: 10.15779/Z38T43J23S.

R. Ibrahim and S. Susanto, "Tantangan Hukum Acara Pidana Indonesia Menghadapi Bukti Elektronik Berbasis AI," Jurnal Masalah-Masalah Hukum, vol. 51, no. 3, pp. 312–325, 2022, doi: 10.14710/mmh.51.3.2022.312-325.

S. Agarwal et al., "Protecting World Leaders Against Deepfakes," in Proc. IEEE/CVF Conf. Comput. Vis. Pattern Recognit. (CVPR) Workshops, 2019, pp. 38–45.

S. Westerlund, "The Emergence of Deepfake Technology: A Review," Technology Innovation Management Review, vol. 9, no. 11, pp. 39–52, 2019, doi: 10.22215/timreview/1282.

T. T. Nguyen et al., "Deep Learning for Deepfakes Creation and Detection: A Survey," IEEE Access, vol. 8, pp. 223273–223324, 2020, doi: 10.1109/ACCESS.2020.3040223.

Y. Mirsky and W. Lee, "The Creation and Detection of Deepfakes: A Survey," ACM Computing Surveys, vol. 54, no. 1, pp. 1–41, 2021, doi: 10.1145/3425780.