AI has a role to play in detecting fake NFTs

Beyond all the good a permissionless internet promises, it also makes it convenient for anyone to freely mint pirated non-fungible tokens (NFTs). There are actually over 90 million fake copies of NFTs. Because in a permissionless system, what’s to stop bad actors from creating copymints to trick unsuspecting users or damage a brand’s reputation?

Just the 20 most copied NFT projects account for 8 million fakes copies across NFT marketplaces.

Since NFTs are valuable only because of their uniqueness, e.g copycat NFTs are fundamentally worthless to consumers. They involve a huge reputational cost in addition to financial loss for buyers and creators. This is particularly detrimental to a nascent and emerging industry such as NFTs.

The “non-fungibility” and rarity of NFT assets is crucial to their value proposition. These are the features that bring long-term users to this domain. But while the on-chain “token” itself may be unique and non-interoperable, the content mapped to it through metadata can be tampered with, replaced, or even removed. This is among the most important technical challenges NFT innovators face today.

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It is clear now that NFT marketplaces must increase to protect the interests of consumers and creators against copying, counterfeiting and infringement of intellectual property rights.

But the big question for them is: How do you protect users from copying while keeping the ethos of a permissionless and decentralized internet intact?

Copyminting has grown alongside NFTs

NFT sales topped 101 million in 2022, nearly 67% higher than in 2021 despite widespread bearish trends. Total monthly NFT trading volume reached $1 billion across marketplaces in January 2023, and the industry is on track to become a $231 billion market by 2030. NFT trademark registrations also hit new highs in 2022, further illustrating the industry’s rapid growth. But the demand for NFTs is increasing not only among users, but also among malicious actors.

Copyminting is among the most common scams involving NFTs. This method involves attackers tricking buyers into thinking their collection is original. Whereas in reality it’s just a copy or rip-off of another NFT, albeit a popular one. Bored Ape Yacht Club, for example, has 10,000 genuine NFTs and more than 4 million fake NFTs.

Most often, copymints simply make minor adjustments to the original collection, such as highlighting, mirroring, adding frames, and pixelating originals. Some other methods include resizing, changing color, and adding unembedded texts or emojis.

Fraudsters also often use filters to create fake NFTs. Sometimes copycats put up pixel-for-pixel copies of accounts that have fake blue ticks and unauthorized copies of brand logos. This makes it even more difficult for users to distinguish between genuine and fake collections.

And with hundreds of NFTs listed across marketplaces every day, manually checking them for fakes is becoming increasingly challenging.

AI can restore authenticity and originality to NFTs

One way to ban fake coins is to abolish the “permissionless” nature of an NFT platform and limit the rights to create NFTs. However, that would go against the Web3 ethos, leaving NFT marketplaces in a tough spot.

NFT marketplaces, brands and creators need solutions that can effectively detect counterfeits without the need to restrict access or gatekeep these platforms. Artificial intelligence-driven content recognition and fraud detection systems work wonders for this purpose.

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They can distinguish between originals and fakes to a degree impossible for the naked human eye. Especially with the ever increasing number of NFT projects, AI models are a game changer against counterfeiting. These solutions can process hundreds of millions of assets per day with 99.9% accuracy.

In fact, some of the biggest NFT marketplaces – including OpenSea and Rarible – have recently started using AI solutions to help with near-real-time copymint detection. This means that the AI ​​solutions can assess new and existing collections for a wide range of parameters. Based on the results, they can detect potentially fake NFTs and either remove them immediately or notify marketplace moderators to take action.

Although copyminting currently plagues stakeholders across the NFT landscape, innovative solutions like these could usher in a better future. By recognizing counterfeits against the immutable on-chain data of the originals, they can restore authenticity and originality of NFTs.

Doing so will go a long way to increasing investor confidence, attracting more institutional capital and boosting adoption. And these are among the most valuable assets for NFTs as they mature into a mainstream industry.

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 herein are those of the author alone and do not necessarily reflect or represent the views and opinions of Cointelegraph.