EWJ August 62 2025 web - Journal - Page 18
Ultimately, AI-driven detection tools are essential in
the battle against deepfakes: using AI to combat AI.
However, their effectiveness hinges on constant vigilance, continuous learning, and adaptation to an
evolving landscape of digital media manipulation.
Regular updates, informed by research and
real-world data, are essential to improving the
effectiveness of these tools.
l Not all forensic artefacts provide clear evidence of
manipulation. Sophisticated AI tools can obscure their
digital fingerprints, leaving behind minimal traceable
evidence.
l When media is uploaded to social media platforms,
it often undergoes compression, leading to the loss or
alteration of original data. This compression can erase
valuable forensic evidence which is crucial for identifying deepfakes.
2. Forensic analysis
While AI-based detection methods focus on content
analysis, there are other forensic artefacts embedded
within a media file which serve as corroborative evidence supporting a file's legitimacy or suggesting fabrication. These forensic artefacts often contain
information about when and where a media file was
created, as well as the device or software used. This
data can help verify the authenticity of content by confirming whether it aligns with expected creation
details, such as time and location.
Conclusion
Deepfakes pose complex challenges to the field of
digital forensics, necessitating an adaptive approach
that blends advanced AI-driven solutions with traditional digital forensic techniques. If you require support in forensically investigating deepfake content,
please contact our team by emailing
dfsupport@s-rminform.com
Author
Ryan Shields
Senior Associate, Digital Forensics
www.s-rminform.com/
Identification of anomalies can signal that a file was
edited or processed through unconventional means.
The presence of certain metadata or patterns (e.g.,
software editing signatures) can be indicators of
known editing tools frequently used to create deepfakes, helping to identify evidence of fabrication.
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While this analysis offers potential in identifying
manipulated content, several complexities make this
approach challenging:
l The wide array of tools available for creating
deepfakes means the extent of residual forensic
artefacts can vary significantly. Different software and
platforms may not leave consistent or identifiable
patterns, complicating the task of establishing a
reliable signature for detection.
EXPERT WITNESS JOURNAL
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