Centralized data networks, those owned and/or managed by a single entity, have been structurally broken for years. Because? Single points of failure. If one entity (or even several) has access to a database, then there is only one “point” to compromise to gain full access. This is a serious problem for networks that contain sensitive data, such as customer information, government files, and financial records, and for those that have infrastructure control, such as power grids.
Billions of digital records were stolen in 2024 alone causing damage estimated at 10 billion dollars! Notable breaches include nearly all of AT&T’s customer information and call logs, half of America’s personal health information, 700 million end-user records from companies using Snowflake, 10 billion unique passwords stored in RockYou24 and Social Security records of 300 million Americans.
Fountain: statesman2024
This is not just a private sector issue: governments and crucial national infrastructure also rely on centralized networks. Notable recent breaches include records of 22 million Americans stolen from the US Office of Personnel Management, sensitive government communications from multiple US federal agencies, personal biometric data of 1.1 billion Indian citizens, and the current Chinese infiltration into several US Internet service providers
Although hundreds of billions of dollars are spent each year on cybersecurity, data breaches are becoming larger and occurring more frequently. It has become clear that incremental products cannot address these network vulnerabilities. the infrastructure must be completely redesigned.
Source: mercado.us2024
AI magnifies the problem
Recent advances in generative AI have made it easier to automate everyday tasks and improve work productivity. But the most useful and valuable AI applications require context, that is, access to the user’s sensitive personal, financial and health information. Because these AI models also require massive computing power, they largely cannot run on consumer devices (computers, mobile devices) and instead must access public cloud networks, such as AWS, to process data requests. more complex inference. Given the severe limitations inherent to centralized networks illustrated above, the inability to securely connect sensitive user data to AI in the cloud has become a major barrier to adoption.
Even Apple pointed this out during its Apple Intelligence announcement earlier this year, stating the need to be able to enlist the help of larger, more complex cloud models and how the traditional cloud model is no longer viable..
They mention three specific reasons:
- Privacy and Security Verification: Vendor claims, such as not recording user data, often lack transparency and compliance. Service upgrades or infrastructure troubleshooting can inadvertently record sensitive data.
- The execution time lacks transparency: Vendors rarely reveal software details and users cannot verify whether the service is running without modifications or detect changes, even with open source tools.
- Single point of failure: Administrators require high-level access for maintenance, which risks accidental data exposure or abuse by attackers targeting these privileged interfaces.
Fortunately, Web3 cloud platforms offer the perfect solution.
Blockchain Orchestrated Confidential Cloud (BOCC)
BOCC networks are like AWS, except they are built entirely on confidential hardware and governed by smart contracts. Although it’s still early days, this infrastructure has been in development for years and is finally starting to incorporate Web3 projects and Web2 enterprise clients. The best example of this architecture is Super Protocol, an off-chain enterprise-grade cloud platform managed entirely by on-chain smart contracts and built on trustless execution environments (TEE). These are secure hardware enclaves that keep code and data verifiably confidential and secure.
Fountain: Super protocol
The implications of this technology address all of Apple’s concerns noted above:
- Privacy and Security Verification: With public smart contracts organizing the network, users can verify whether user data was transported and used as promised.
- Workload and program transparency: The network also verifies work performed within sensitive TEEs, cryptographically proving that the correct hardware, data and software were used and that the output was not tampered with. This information is also sent on a chain so that everyone can audit it.
- Single point of failure: Network resources (data, software, hardware) can only be accessed using the owner’s private key. Therefore, even if a user is compromised, only that user’s resources are at risk.
While cloud AI represents a huge opportunity for Web3 to be disruptive, BOCCs can be applied to any type of centralized data network (power grid, digital voting infrastructure, military IT, etc.), to provide privacy and superior and verifiable security, without sacrificing performance. or latency. Our digital infrastructure has never been more vulnerable, but blockchain orchestration can fix it.
