Centralized deepfake detectors are failing against crypto scams. Blockchain-based detection networks offer the only scalable defense against AI fraud.
Opinion
Opinion by: Ken Miyachi, founder of BitMind
Centralized deepfake detectors are structurally misaligned, brittle and falling behind. The crypto industry needs a crypto-native defense — decentralized detection networks that reward many independent model providers for catching real-world fakes and record those judgments onchain.
The result: Transparency and composable use across exchanges, wallets and decentralized finance (DeFi).
Q1 alone saw stolen through deepfake scams, with of high-value crypto fraud now attributed to AI-generated impersonations.
As criminals use deepfakes to bypass KYC processes and impersonate executives in fraudulent transfers, the crypto industry faces an existential threat that centralized detection systems cannot solve.
Centralized detection is failing
The core failure is architectural.
Centralized detectors are conflicted and siloed, with vendor-locked systems detecting their model outputs best while missing others. When the same companies build both generators and detectors, the incentives become blurred. These detectors are static and slow as opposed to their decentralized counterparts, and train against last month’s tricks as adversaries iterate in real-time.
Crypto cannot outsource this to the same closed systems that deepfakes outpace without expecting the same pitfalls. It’s time to change that mentality and shift to decentralized detection networks.
Law enforcement agencies across Asia dismantled deepfake scam rings, which used AI-generated deepfakes to impersonate figures like Elon Musk and government officials. The scams have evolved to include live deepfake impersonations during video calls, where fraudsters pose as blockchain executives to greenlight unauthorized transactions.
For example, Strategy executive chairman, Michael Saylor, last year warned that his team removes approximately 80 fake AI-generated YouTube videos impersonating him daily, promoting bogus Bitcoin giveaways via QR codes, highlighting how persistent these attacks are on social platforms.
Bitget CEO Gracy Chen it herself, “The speed at which scammers can now generate synthetic videos, coupled with the viral nature of social media, gives deepfakes a unique advantage in both reach and believability.”
Related:
When traditional detection tools achieve only accuracy on real-world deepfakes, it creates a massive blind spot that criminals exploit. OpenAI CEO Sam Altman recently of an “impending fraud crisis” because AI has “defeated most authentication methods.” The crypto industry needs solutions that evolve as quickly as the threats themselves.
These vulnerabilities even extend to emotional manipulation, as seen in AI-powered where deepfakes and chatbots fabricate personal relationships to extract funds.
The fundamental problem lies in trusting major AI companies to self-regulate their own outputs amid political and economic pressures. Google’s SynthID only detects content from its own Gemini system, ignoring deepfakes from competing tools. Conflicts of interest become inevitable when the same companies that create generative AI also control detection systems.
A March 2025 found that even the best centralized detectors dropped from 86% accuracy on controlled data sets to just 69% on real-world content. These static systems train once on existing databases and expect to work forever, but criminals adapt faster than centralized authorities can respond.
A decentralized, crypto-native defense
Decentralized detection networks represent true blockchain principles applied to digital security. Just as Bitcoin solved the double-spending problem by distributing trust, decentralized detection solves the authenticity problem by distributing verification across competing miners.
Platforms can enable this approach by creating incentive mechanisms where AI developers compete to build superior detection models.
The crypto-economic rewards automatically direct talent toward the most effective solutions, with participants compensated based on their models’ actual performance against real-world deepfakes. This competitive framework has demonstrated significantly higher accuracy on diverse content compared to centralized alternatives, achieving results that static systems cannot match.
A decentralized verification approach becomes essential as the generative AI will become a market by 2032, requiring scalable authentication mechanisms that match AI’s rapid development.
Conventional methods are easily altered or bypassed, while centralized databases are prone to hacks. Only blockchain’s immutable ledger provides the transparent, secure foundation to combat the projected surge in AI-driven crypto scams.
Deepfake scams could represent of crypto crimes without decentralized detection protocols by 2026. Attacks like the OKX account drain via AI impersonation demonstrate how vulnerable centralized exchanges remain to sophisticated deepfake attacks.
DeFi platforms face particular risk since pseudonymous transactions already complicate verification.
When criminals can generate convincing AI identities for or impersonate protocol developers, traditional security measures prove inadequate. Decentralized detection offers the only scalable solution that matches DeFi’s trustless principles.
Regulatory alignment and the path forward
Regulators increasingly demand robust authentication mechanisms from crypto platforms, with decentralized detection networks already offering consumer-facing tools that instantly verify content. Why not work alongside the companies providing auditable, transparent verification that even satisfies the regulatory requirements while maintaining the permissionless innovation that drives blockchain adoption?
The blockchain and cryptocurrency sector faces a critical juncture: either stick to centralized detection systems that inevitably trail criminal ingenuity or adopt decentralized architectures that transform the industry’s competitive incentives into a powerful shield against AI-fueled fraud.
Opinion by: Ken Miyachi, founder of BitMind.
This article is for general information purposes and is not intended to be and should not be taken as legal or investment advice. The views, thoughts, and opinions expressed here are the author’s alone and do not necessarily reflect or represent the views and opinions of Cointelegraph.
