Securing Digital Media in the Age of AI and Deepfakes: A Hardware-Based Solution

The current capabilities of deepfake and Artificial Intelligence (AI) technologies make it difficult to distinguish what is original from what is fabricated. Electronic documents can be digitally signed to verify and authenticate their information, making them admissible as evidence in court. In contrast, images and videos from Internet of Things (IoT) devices-such as police body cameras, security cameras, and smartphones are susceptible to deepfake manipulation, which can undermine their authenticity in legal proceedings. This research hypothesizes that digitally signing image and video data utilizing hardware cryptographic coprocessors could render them admissible in court. Utilizing our processes will also identify if any manipulation of the image data has occurred. Our approach addresses a critical need in the justice system to combat the challenges deepfakes pose and could pave the way for enhanced trust in digital evidence, bolstering the integrity of the judicial process.

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Publication Details

Published
2025-03-22
DOI
https://doi.org/10.1109/southeastcon56624.2025.10971593
Citations
1
Primary Topic
Advanced Malware Detection Techniques
Type
article
Field-Weighted Citation Impact
1.49
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article

Securing Digital Media in the Age of AI and Deepfakes: A Hardware-Based Solution

Steven Puckett, Eric Scott Sisson
1 citations
Advanced Malware Detection Techniques
1.49
article

Securing Digital Media in the Age of AI and Deepfakes: A Hardware-Based Solution

Steven Puckett, Eric Scott Sisson
article en
1 citations

Abstract

The current capabilities of deepfake and Artificial Intelligence (AI) technologies make it difficult to distinguish what is original from what is fabricated. Electronic documents can be digitally signed to verify and authenticate their information, making them admissible as evidence in court. In contrast, images and videos from Internet of Things (IoT) devices-such as police body cameras, security cameras, and smartphones are susceptible to deepfake manipulation, which can undermine their authenticity in legal proceedings. This research hypothesizes that digitally signing image and video data utilizing hardware cryptographic coprocessors could render them admissible in court. Utilizing our processes will also identify if any manipulation of the image data has occurred. Our approach addresses a critical need in the justice system to combat the challenges deepfakes pose and could pave the way for enhanced trust in digital evidence, bolstering the integrity of the judicial process.

University of North Alabama (US), Mississippi State University (US)
Openalex Percentile: Top 20%
Advanced Malware Detection Techniques
1.49
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