Research On Forensic Investigation Of Ai-Generated Deepfake Audio, Video, And Images In Criminal Proceedings
Case 1: Maryland, USA – School Principal Audio Deepfake
Facts:
A former high school athletics director created an AI-generated audio clip that made the school principal appear to make offensive and discriminatory remarks.
The clip was circulated among students and staff, causing reputational harm and threats to the principal.
Forensic Investigation:
Voice biometrics were used to compare the principal’s genuine voice to the deepfake audio.
Metadata analysis and distribution tracing helped identify the source and propagation of the clip.
Investigators confirmed the audio was artificially generated using voice-cloning software.
Legal Outcome:
The perpetrator entered an Alford plea, acknowledging wrongdoing without admitting guilt.
Sentenced to four months in jail for misdemeanor disruption of school operations.
Lessons Learned:
Deepfake audio alone can cause significant harm and is legally actionable.
Forensic analysis must include technical voice comparison and metadata tracking.
Case 2: India – Rashmika Mandanna Deepfake Video
Facts:
A deepfake video was created showing actress Rashmika Mandanna in inappropriate content.
The video circulated widely on social media, prompting her to file a complaint.
Forensic Investigation:
Technical analysis revealed facial swap artifacts and inconsistencies in lighting and movement.
Social media accounts and IP addresses were traced to the perpetrator.
Metadata confirmed manipulation and unauthorized use of images.
Legal Outcome:
The accused, a 24-year-old, was arrested under Indian Penal Code (IPC) sections for forgery and identity theft, as well as the IT Act provisions for privacy violations.
Lessons Learned:
Celebrity deepfakes used for harassment or social media gain are prosecutable.
Timely forensic intervention is crucial to track distribution and preserve evidence.
Case 3: India – Ranveer Singh Deepfake Political Endorsement
Facts:
A video circulated making actor Ranveer Singh appear to endorse a political party.
The actor publicly denied involvement and filed a complaint.
Forensic Investigation:
Frame-by-frame video analysis identified AI manipulation of facial expressions.
Voice analysis detected mismatches with the actor’s authentic voice.
Platform logs were traced to the original uploader to establish intent.
Legal Outcome:
Charges included cheating, forgery, and IT Act violations.
The case highlighted the potential misuse of deepfakes to influence political opinion.
Lessons Learned:
Deepfakes in political contexts can have wide-reaching consequences.
Investigations must combine multimedia forensics and legal expertise for attribution.
Case 4: Meerut, India – Police Officer Deepfake Harassment Video
Facts:
An AI-generated video depicted a senior police officer in a compromising situation with an accused criminal.
The video was circulated to damage the officer’s reputation.
Forensic Investigation:
Investigators confirmed the video was AI-manipulated and not real footage.
IP tracing and device logs helped identify the perpetrator.
Metadata analysis and visual artifact detection were key in proving the video was fabricated.
Legal Outcome:
FIR registered under IT Act provisions related to defamation and digital harassment.
The case emphasized the use of deepfakes to target law enforcement officials.
Lessons Learned:
Deepfakes can be used to harass or frame public officials.
Prompt forensic investigation is essential to prevent further spread.
Case 5: Hypothetical U.S. Deepfake Financial Fraud Case
Facts:
An AI-generated deepfake video and audio were used to impersonate a company CEO to authorize fraudulent wire transfers.
The attackers tricked financial staff into transferring funds to offshore accounts.
Forensic Investigation:
Audio analysis detected anomalies inconsistent with the CEO’s speech patterns.
Video artifacts such as unnatural blinking and face misalignment were identified.
Internal network logs traced the origin of the attack to an external server.
Legal Outcome:
The perpetrators were charged with wire fraud, identity theft, and computer crimes.
The case demonstrated the financial sector’s vulnerability to deepfake-enabled social engineering.
Lessons Learned:
Deepfakes pose a significant risk for financial and corporate fraud.
Organizations need verification protocols and AI-based detection systems.
Summary Analysis Across Cases
| Case | Media Type | Crime | Forensic Focus | Legal Takeaway |
|---|---|---|---|---|
| Maryland Principal | Audio | Harassment | Voice biometrics, metadata | Audio deepfakes are actionable |
| Rashmika Mandanna | Video | Identity theft/forgery | Facial swap detection, IP tracing | Social media deepfakes prosecutable |
| Ranveer Singh | Video & Audio | Political misrepresentation | Frame & voice analysis | Deepfakes can influence politics; attribution key |
| Meerut Officer | Video | Defamation/harassment | Video artifact & IP tracing | Deepfakes target public officials; fast response critical |
| CEO Fraud | Video & Audio | Financial fraud | AI detection, network tracing | Deepfakes threaten corporate security; verification protocols essential |
These cases show that forensic investigation combines multimedia analysis, metadata, AI detection, and chain-of-custody documentation, while legal proceedings adapt existing laws to address AI-generated evidence.
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