Introducing A High Value Data Vision For The Future

I.

In today’s digital landscape, the increasing value of data has led to a growing fragmentation of trust, especially around high value data. As organizations and individuals become more reliant on digital systems to store, process, and transmit sensitive data, concerns around privacy, security, and data integrity are at an all-time high. In this post I’m going to uncover how our shifting landscape of high value data is reshaping the paradigms of privacy and security and how we must transition to a trust-minimized decentralized system. But first, we must define exactly what high value data is.

"High Value Data (HVD) refers to data that is extremely valuable to an organization or individual due to its potential to significantly impact everyone’s lives – from AI to trading information (leverage and limit orders) to identity to healthcare data to access control to decentralized social to passwords to biometrics – high value data is woven into the infrastructure of our society."

II.

Web3 is cementing itself as a new layer of the internet, underpinned by blockchains and decentralized infrastructure. The value proposition of blockchains themselves has remained relatively unchanged – public ledgers with shared global state optimized for use cases like transactions where consensus on order is critical. Cryptographers and protocol developers have stepped up to solve hard scaling problems and push the efficiency of smart contract chains, with the theoretical ~[endgame]~ for blockchain scaling seeming to be in sight. 

Decentralization is growing to mean far more than that though, with networks being designed to apply trust-minimized and fault-tolerant design to niches like file storage (IPFS and the Permaweb), compute networks (Render Network and Gensyn), and much more. These layers of experimentation are pushing what’s possible for builders in the space and introducing new types of compute models, but they tend to fall short of the needs of many real-world use cases by relying on the same fully transparent data models that popular blockchains do.

New research in privacy-enhancing technologies (PETs) will shift the tide. Zero knowledge proofs are being leveraged to add varying amounts of confidentiality to movements on the ledger, granting a much needed layer of transaction privacy to users. Trusted execution environments (TEEs) are gaining popularity as a band-aid solution to privacy when searching for stronger security models. Fully homomorphic encryption (FHE) is getting retrofitted onto existing blockchain tech.

But why must privacy just be an ideological afterthought to tack onto existing blockchain transactions and compute models? 

Data privacy can be a tool that opens up the design space of what is possible with trust-minimized networks. The notion of ‘privacy’ in web3 has become synonymous with private currencies and preventing on-chain traceability. These protocols are exceedingly important parts of the ecosystem that are necessary for crypto to thrive, but privacy and security are also important tools for onboarding real-world use cases and enabling novel on-chain applications, especially in the context of data. PETs can disintermediate the privileged actors that control the flow of the world’s high value data, while retaining or even expanding the data’s utility for users and developers. Imagine a world of user-controlled social media, auditably neutral financial dark pools, and AI models whose use of your data is dictated by cryptography rather than lopsided commercial incentives.

III.

Centralized architectures offer too many compromises; they’re plagued with bureaucratic inefficiencies and potential misuse. The consequences of such high concentrations of power have been starkly highlighted by incidents like Cambridge Analytica, where data was heavily manipulated at scale to influence major political events as well as significant data breaches like the 2022 LastPass and 2020 Ledger hacks that exposed the sensitive details of millions.

These events underscore the urgent need to reevaluate our views on data. Shifting focus from merely defending against hacks to fundamentally rethinking data stages and processing is critical. A move away from centralized models to decentralized systems can address key concerns. Decentralized technologies promise not only enhanced security but also minimize trust placed on single points of failure, thereby mitigating risks of misuse. 

We as a digital society need to broaden our perspective beyond just the traditional web2 cybersecurity strategies. We need to explore solutions that emphasize trust-minimization, censorship resistance, fault tolerance, confidentiality, and data integrity. This forward thinking approach is not just about defending against sophisticated threats but perhaps more importantly about creating a robust, resilient, and equitable data ecosystem. I believe that emerging decentralized technologies and web3 frameworks are at the forefront of this transfer.

IV.

High value data as a category is a significant opportunity to expand the impact of web3, both within the crypto ecosystem as well as an alternative to traditional centralized systems. Web3 has made significant inroads into transaction privacy (as distinct from data privacy), but is still grappling with the central tension between transparency and providing the legitimate privacy which enables real world use cases. On the other hand, traditional centralized entities have struggled with safeguarding high value data, which has led to significant breaches that highlight the  opportunity for a fundamentally new approach to data security. In both contexts, high value data is not just a technical challenge; it is an opportunity to change  the trust assumptions and systemic integrity of the world’s digital ecosystem. 

Put simply, securing high value data is fundamental to safeguarding our personal data, digital identities, passwords and financial assets, all of which are integral to the fabric of our digital lives. The continual expansion of web3 into use cases beyond transactions hinges on how effectively we can navigate these complex secure data storage and computation waters, making this an endeavor that deserves collective attention and effort.