Synthetic-media detection (deepfakes protection)
We implement synthetic-media detection — tools that help identify AI-generated images, video and audio (deepfakes): checking uploaded content, protection from face/voice forgery, screening for manipulation. For trust and fraud protection. Honestly upfront: this is an ARMS RACE — detectors are imperfect and quickly become outdated: new generative models bypass old detectors; detection is NOT one hundred percent (there are false positives and misses); it is risk reduction and a signal to verify, not guaranteed protection from all fakes.
Synthetic-media detection (deepfakes protection) — overview
Synthetic-media detection is integrating tools and processes to identify content generated or altered by AI: detecting deepfake images/video (face swaps, manipulation), synthetic voice (important against voice fraud), screening user-uploaded content, authenticity verification in sensitive scenarios (KYC, moderation, anti-fraud). Honestly about the arms race, this is key: synthetic detection is a continuous competition of generators and detectors. Generative models improve fast and learn to bypass existing detectors, so any detector becomes outdated over time and requires updating. 'Installed a detector and protected forever' is untrue. Honestly about imperfection: detectors do NOT give 100% accuracy. There are false positives (took the real for a fake) and misses (did not recognize a fake) — especially on new, high-quality forgeries. So a detector's result is a signal/probability for further verification, not a final verdict 'fake/not fake'. In critical cases human review and additional signals are needed. Honestly about the effect: it noticeably raises the chances of catching forgeries and reduces fraud risk, especially mass and not the most sophisticated, but does not guarantee detecting all fakes (especially targeted, newest). Honestly about the link: this is detecting OTHERS' synthetic media; marking the provenance of YOUR content is a separate task (provenance 908). Honestly about updating: detectors must be regularly updated following new generators — a process, not a one-off install. Honestly about access: verification scenarios and integration are needed. An important boundary: this is fake detection; provenance of your content — 908; computer vision — 879. Picture this: instead of 'any deepfake passes unnoticed' — screening that raises the chance of catching a forgery (with an honest understanding that not all). The base price starts from 50,000 ₽ (depends on media types and scenarios).
Problems we solve
- Deepfakes (face/voice) can pass as real.
- Uploaded content is not checked for synthetics.
- Voice/visual fraud is a growing risk.
- No forgery-screening process in sensitive scenarios.
What's included in the Synthetic-media detection (deepfakes protection) service
- Detection of synthetic images/video/audio (deepfakes)
- Screening uploaded content for manipulation
- The result as a signal/probability for verification (not a verdict)
- Human review in critical cases
- Honest boundaries (arms race; not 100%; false positives/misses)
- Regular detector updating (following generators)
- A link with provenance (908) as a separate task
- Handover and review with you
What you get
- Content screening for synthetics and deepfakes
- A higher chance of catching a forgery and reducing fraud
- A signal to verify + a human for the critical
- Honest boundaries (risk reduction, not a guarantee of detecting all)
How the work goes: steps
- We define verification scenarios and media types; collect access
- We integrate detectors, set the threshold and human review
- We build in updating, honestly set boundaries with you
Why PDV Expert
- Fixed price and timeline — no surprises on the invoice.
- Report and recommendations in plain language — clear without a technical background.
- In touch at every step and answering questions about the result.
FAQ
Will the detector catch all deepfakes?
No, and that is honest: synthetic detection is an arms race. Generative models quickly learn to bypass detectors, so there is no 100% accuracy: there are false positives (took the real for a fake) and misses (did not recognize a fake), especially on new high-quality forgeries. It is risk reduction and a signal to verify, not guaranteed protection from all fakes. Whoever promises 'we will catch any deepfake' is misleading.
Installed a detector — and can forget it?
No, honestly: detectors become outdated. New generative models bypass old detectors, so they must be regularly updated following the development of generators. 'Installed and protected forever' is untrue. It is a process with maintenance. We honestly build in updating rather than pass off a one-off install as eternal protection.
Can the detector's verdict be fully trusted?
No — the result is a signal/probability, not a final verdict. Due to false positives and misses you cannot automatically and unconditionally block/pass by one detector, especially in critical scenarios (KYC, anti-fraud). There human review and additional signals are needed. We build detection as help in deciding, not as an infallible automaton.
About the provider
The «Synthetic-media detection (deepfakes protection)» service is provided by PDV Expert — a team specialising in «Site quality». We work under contract and deliver a written report with recommendations.