What is Confidential Computing and What are its Limitations

First, let's talk about data. When we discuss data, we typically think of three different states: at rest, in use, and in transit: 

Data at rest: 

This is when data is stored or not actively moving from device to device or network to network. 

Data in use: 

When data is in use, it is being updated, processed, accessed and read by a system. It's the most vulnerable form of data when accessible by one or more users. 

Data in transit: 

In transit, data is moving across a network, being transferred between locations or systems. 
 

If you only protect one or two stages, you still leave room for vulnerabilities and unauthorised access. The question is: Do I need to protect data in all states? You can choose not to encrypt your data at rest, for example. However, it is highly recommended to encrypt the data to eliminate possible security incidents and the headaches that come with them: legal penalties, customer loss, market value, and reputation. 
 

What is Confidential Computing? 

Confidential computing is a set of technologies and practices that protect data while it is being processed, ensuring that sensitive data is never exposed to the system or any third-party components. According to the CCC definition, "Confidential Computing protects data in use by performing computation in a hardware-based, attested Trusted Execution Environment". 

It ensures that sensitive data is protected and secure, helping organisations comply with data privacy regulations and certifications, providing enhanced security and protecting sensitive data from cyber threats. 
 

What are the limitations of Confidential Computing? 
 

Although widely available for use in enterprises and by data centres for cloud platforms, most limitations surrounding Confidential Computing involve scope, cost, performance and complexity: 

Limited Scope: It only protects data within the computing process, but  does not secure the data outside the enclave or protect against physical attacks. Data can still be vulnerable to attacks at other lifecycle stages, such as in transit or at rest. 

Cost: Implementation can be expensive, especially for smaller organisations or companies with limited resources. The cost of hardware, software, and specialised personnel is a significant adoption barrier. 

Malicious Insiders: Confidential computing cannot protect against malicious insiders with unauthorised access to the system. They can manipulate data or access the system, compromising data privacy and security. 

Performance Overhead: Additional overhead and reduced performance are limitations for high-speed data processing applications. Also, it might be challenging to scale the technology for larger data sets. 

Complexity: Confidential computing can be complex to implement and manage, requiring specialised knowledge. That comes as a limitation for organisations that need more resources. 

It is essential to evaluate these limitations when considering implementing this technology for cybersecurity and data privacy. 
 

How about Cryptography? How can Encryption protect my data? 

For years, enterprises focused on issues that complicated the adoption of large-scale encryption techniques, but research has matured tremendously over the last decade. Fully Functional Data-In-Use Encryption eliminates the security versus performance tradeoff by protecting data at rest, in use, and in transit, with simplicity and scalability. 

With the significant increase in data privacy regulations and sophisticated data breaches targeting even the largest tech enterprises, we will see encryption technologies continue to strengthen over the next few years. 

Moreover, as companies rely more on public and hybrid cloud services, market adoption will undoubtedly rise, with organisations from industries across financial services, healthcare, insurance, and more benefiting from protecting sensitive data workloads. 

How can Vaultree help? 

Vaultree's solution is based on the latest cryptographic breakthroughs, enabling companies to perform computations and search on encrypted data without the need to decrypt data: we protect data at all times, at rest, in use, and in transit. 

Now, companies can unlock the full potential of encryption without compromising privacy, security and performance. 

Data-in-Use Encryption vs Confidential Computing

Overall, Vaultree's Fully Functional Data-in-Use Encryption provides better and safer protection for data than confidential computing. Here's why: Data-in-Use Encryption protects data throughout its entire lifecycle - in transit, at rest and in use - whereas enclaves and confidential computing only protect data while being processed. 

Vaultree's new approach to using sensitive data in previously impossible ways is both secure and privacy-preserving. Compared to enclaves and confidential computing, it has minimal overhead and high performance, making it scalable for larger data sets. It's also less complex since enclaves and confidential computing are usually a hurdle to implement and manage. 
 

Vaultree’s solution is designed to be plug-and-play and can be integrated into existing data pipelines without any company infrastructure changes and complex intermediaries. 

It provides complete privacy and security for sensitive data, ensuring it always remains protected.

This solution unlocks the full potential of sensitive data, allowing companies to generate insights and analytics that were previously impossible. It is also significantly faster than traditional encryption methods with no noticeable delays in data processing speeds compared to processing unencrypted data, enabling companies to extract insights and analytics from their data more quickly, improve their business outcomes, and unlock new revenue streams. 

Book a demo, and be amongst the first to witness the encryption revolution.