Blockchain Trend

Combating digital deception

How blockchain can tackle the growing threat of deepfakes

Cyber deception has reached a new level of sophistication, and the rise of deepfake technology is making it harder to trust online content. From manipulating videos and audio to fabricating text, AI-generated forgeries pose serious risks to individuals, organizations, and industries. As the technology behind deepfakes improves, the threat of fraud and misinformation will only increase, making robust, immutable authentication systems more critical than ever.

Blockchain offers a promising solution to this emerging crisis.

300%

Growth in deepfake attacks in the US

70%

Adults not confident they can identify deepfake voice

30%

US businesses attacked by deepfakes

53%

Adults share voice online every week

25%

Adults impacted by deepfake attacks

25%

Victims of AI voice scams who lost money

What are deepfakes and how are they used?

Deepfakes are synthetic media that appear authentic but have been altered or entirely created using artificial intelligence. Here's a look at how each form operates.

Audio:
Using AI to replicate voices, deepfake audio can convincingly mimic real people, sometimes with as little as a minute of voice samples. This poses a particular threat to industries relying on voice biometrics for identity verification, such as banking and customer service.

Video:
By training neural networks on vast datasets of videos and images, criminals can create realistic videos of individuals, including executives, to bypass security systems or spread false information. These videos are often used in fraud, impersonation, and misinformation campaigns.

Images:
Fake images can alter documents or manipulate profiles, enabling criminals to bypass Know Your Customer (KYC) and Anti-Money Laundering (AML) protocols, often for financial fraud.

Text:
AI-generated text mimics human writing, enabling large-scale social engineering, phishing attacks, and document forgery. These models can create convincing fake emails, reports, or articles that fool both individuals and automated systems.

The potential damage caused by deepfakes
is evident.

In 2023, a fake image depicting an explosion at the Pentagon briefly triggered panic on the US stock market. As the technology becomes more accessible and sophisticated, the potential for widespread harm increases. From impersonating company executives to spreading fake news on social media, deepfakes threaten to erode trust in digital media.

Blockchain technology has the potential to provide a powerful defense against deepfakes.

Immutability:

Once data is stored on a blockchain, it cannot be altered without the consensus of the network. This ensures any tampering with media files is easily detectable, as any change produces a new cryptographic hash.

Decentralization:

Unlike centralized systems, blockchain relies on a distributed network of nodes. If one node is compromised, others will reject the tampered data, making the system harder to manipulate.

Transparency:

Public blockchains offer an open history of transactions, allowing users to trace the origin of media files and verify their authenticity. This transparency helps distinguish genuine content from deepfakes.

Cryptographic Security:

Blockchain's advanced cryptographic techniques, encryption, digital signatures, and key management, ensure that media stored on the blockchain is protected and tamper-proof. These methods make it nearly impossible to forge or alter content without leaving a trace.

Data stored on blockchains is fully immutable, meaning the data cannot be changed without consensus from the network.

This consensus is achieved by applying a set of rules that allows network nodes to confirm or deny the validity of state on the blockchain, ensuring that everyone has an identical record of data without requiring a centralized entity. When media is hashed and stored on the blockchain, the chain's immutable ledger makes detection of unauthorized tampering simple, as any change to the content produces a new hash.

By using nodes to distribute data, blockchain networks eliminate single points of control, decentralizing the system. Each node has a copy of the blockchain, and if the node's copy is tampered with, most nodes will reject it. Decentralization makes systems significantly more difficult to breach or disrupt, enhancing the threat detection process.

All public blockchains offer a transparent history of transactions. This open visibility enables users to verify the origin of all previous transactions and media files on the distributed system, making it easier to distinguish genuine content from deepfakes.

The cryptographic security techniques of blockchain - encryption, digital signatures, and key management - make it an ideal system to store and transfer media and content. Encryption uses complex algorithms to protect media that interacts with the chain, allowing users to verify the authenticity of media. The use of digital signatures allows users to confirm that the media was uploaded by a trusted source, as that source must digitally sign off on the public release of the media file. Private keys, managed by hardware modules or digital multi-signature wallets, are used to verify content and sign off on its release. These security techniques make it nearly impossible to deploy deepfake content without clear evidence of media tampering.

Institutional efforts are underway to ensure the provenance of media and data with the use of blockchains. Microsoft and the BBC have teamed up to launch Project Origin, an initiative that utilizes the technology to combat deepfakes and the spread of misinformation. This cross industry approach leverages decentralization for the authentication of content. The New York Times launched its own internal project to mitigate these threats with the use of distributed ledger technology. The project provides transparent metadata for content, enabling consumers to validate the source of information and identify if any alterations have been made.

How enterprises can manage Deepfake risks

Tools prevent, detect, and mitigate impact of deepfake attacks

Deepfake image / video detection

AI/ML techniques that analyze physical markers, optical flow, and facial symmetry to determine real from AI-generated images.

Deepfake audio detection

AI/ML techniques that analyze an audio clip to detect whether it is authentic or artificial.

Content watermarking

A digital metadata stamp imposed to distinguish fake from real content.

Identity verification

Fraud-prevention techniques that detect spoof/deepfake identities during identity verification.

Brand protection and content licensing

Tools that safeguard brand identity and enable licensing of proprietary content.

Narrative attack protection

Multichannel analysis leveraged to detect, monitor, and mitigate disinformation attacks.

The startup landscape is populated with many innovative, blockchain-enabled solutions.

Recently, OpenOrigins raised $4.5 million to deliver content authentication services. The company provides users with full ownership of their own media by cryptographically proving the source of the media. Their "tamper-proof" ledger stores proofs, safeguarding the record in perpetuity. The platform also allows users to monetize their archives, as authenticated content can be licensed as copyright compliant material used to train Al models.

We are at a unique time in history. Every layer in the AI stack is improving exponentially, with no signs of a slowdown in sight. As a result, many founders feel that they are building on quicksand. On the flip side, this flywheel also presents a generational opportunity. Founders who focus on large and enduring problems have the opportunity to craft solutions so revolutionary that they border on magic.

Ashu Garg, General Partner at Foundation Capital

While blockchain presents a powerful tool against cyber deception, mass adoption remains a challenge.

The success of blockchain-based solutions depends on large-scale buy-in from platforms, media outlets, and consumers. In addition, these systems will need to adapt continuously as deepfake technology evolves.

Blockchain is just one part of the broader solution to combat digital deception. Governments, tech companies, and media organizations must also implement regulatory frameworks and ethical guidelines for AI development to prevent the malicious use of deepfake technology. Blockchain is poised to become a key component in the fight against digital deception, providing businesses, consumers, and journalists with confidence in the authenticity of content.