As tokenised economies gain traction, safeguarding user privacy and data security is more critical than ever. Jeremy Bradley, COO of Zama, explores the role advanced privacy-preserving technologies are playing in the trust-building process
As tokenised economies gain traction, safeguarding user privacy and data security is more critical than ever. Jeremy Bradley, COO of Zama, explores the role advanced privacy-preserving technologies are playing in the trust-building process
For me, tokenisation is a transformative force for the digital economy, with decentralised systems and new forms of asset ownership opening the door to fractional ownership, enhanced liquidity, and broader access to financial systems. And I’m not alone in that thought. The tokenised economy is expanding, and fast—by 2027 it’s forecast to exceed $24 trillion in asset tokenisation.
However, a key issue remains, becoming ever more critical as this expansion develops: how to secure user identities and sensitive data while upholding privacy standards. Right now, the main issues include:
If privacy and security are neglected, the very foundation of trust that underpins the tokenised economy would crumble. Not only would platforms that fail to address privacy concerns risk being overtaken by those that prioritise security, but there’d be reduced adoption overall, with both enterprises and individuals hesitant to engage with any insecure systems on the scene.
Should privacy breaches occur, it could also lead to significant financial losses and undermine confidence in tokenised ecosystems, while governments could impose prohibitive restrictions that may hinder innovation.
Tackling trust with tech
On the upside, there are a number of emerging privacy-preserving technologies that can help solve this challenge.
Firstly, let’s look at Fully Homomorphic Encryption (FHE) – an encryption method that enables data to remain encrypted even during processing – which is a potential cornerstone for secure, decentralised environments.
With FHE, every stage of tokenisation – asset creation, transfer, and smart contract execution – can occur on encrypted data, perfectly aligning with the privacy needs of tokenisation platforms.
FHE can also enable computation on encrypted data within smart contracts, allowing for complex functionalities without compromising privacy, and can integrate seamlessly into existing Layer 1 or Layer 2 solutions, enhancing their security without redesigning entire systems.
Alongside FHE, there are also a number of other complementary technologies that contribute to privacy and security. These include:
Challenges and how they’re being addressed
While at first glance it may seem as though a solution to the trust issues plaguing tokenised economies is ready and waiting – but there is still work to be done before these technologies can be implemented at scale.
Performance overheads are a significant barrier, as the computational intensity of cryptographic methods like FHE can lead to latency issues that hinder real-time processing. Additionally, blockchain integration poses a technical hurdle, requiring these technologies to align seamlessly with decentralised consensus mechanisms without compromising performance or security.
Usability is another pressing issue, as developers often face steep learning curves when working with these advanced tools, which can slow adoption and innovation. Finally, interoperability remains a persistent challenge, as ensuring that privacy-preserving technologies can function across diverse blockchain ecosystems demands standardisation and robust cross-platform solutions.
However, right now efforts to overcome these challenges are already making significant progress. Advancements in FHE algorithms are underway, aiming to reduce computational overhead and bring the possibility of real-time privacy closer to reality, while the development of developer-friendly tools is a top priority for the industry, so that we can address usability issues. By creating intuitive SDKs and APIs, we aim to empower developers to integrate FHE seamlessly into their applications without requiring deep cryptographic expertise.
Additionally, collaboration with blockchain communities is underway in an effort to create a standardised approach to privacy-preserving technologies, ensuring interoperability and accelerating adoption across diverse platforms.
With these initiatives underway, privacy-preserving technologies like FHE have incredible potential to address the security issues within tokenised economies. But the key is to take a layered approach – to combine FHE with the likes of ZKPs, MPC, and Differential Privacy to build a scalable, secure foundation where tokenised economies are not only efficient but also secure, private, and inclusive.
Only then can we not only drive mass adoption and ensure the growth of a digital economy – but ensure that this digital economy is one that we can trust.
Tokenisation is the process of converting rights to an asset into a digital token on a blockchain, enabling fractional ownership and increased liquidity in financial markets.
Fully Homomorphic Encryption (FHE) is a form of encryption that allows computations to be performed on encrypted data without needing to decrypt it, enhancing privacy and security.
Differential Privacy is a method that adds statistical noise to datasets to protect individual privacy while still allowing for meaningful data analysis.
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