Confidential Computing: Redefining Data Security for a Privacy-First Era

As industries such as finance, healthcare, and cryptocurrency increasingly rely on cloud infrastructure, traditional security models that focus on network perimeter defences are proving insufficient for safeguarding sensitive data. This article discusses how confidential computing is transforming data security by protecting both data and applications during processing.

Read on to explore the distinctions between traditional security models and confidential computing, and to gain a better understanding of the challenges on the horizon for organisations looking to enhance their data protection strategies.

Traditional Security Models

Traditional perimeter-based security models aim to protect data by securing the boundaries of the network and implementing measures such as firewalls, intrusion detection systems, and encryption of data at rest.

These methods, while effective for many scenarios, struggle to address insider threats, unauthorised access during data processing, and sophisticated attacks on vulnerabilities within processing environments. This gap leaves sensitive data exposed, even within a seemingly secured network perimeter. In response to these shortcomings, confidential computing has emerged as a paradigm shift in data security.

Isolating Trust with TEEs

By isolating data and applications during processing through trusted execution environments (TEEs) - also called secure enclaves, confidential computing extends protection beyond traditional encryption measures. Through hardware-level isolation, TEEs protect data while it is in use—a capability traditional models lack.

These TEEs, which include technologies such as Intel’s SGX, AWS Nitro Enclaves, and Azure Confidential VMs, create isolated environments that prevent unauthorised access to data and the code operating on it.

This isolation ensures that data is only accessible to authorised applications running within the enclave. Crucially, even cloud providers or privileged users cannot access or view the data or code within the TEE, offering a robust layer of protection against insider threats. TEEs also leverage cryptographic attestation, a verification method that ensures only authorised code is executed within the enclave. This attestation provides proof to external entities that the application within the TEE is authentic and untampered. It’s a vital capability for organisations handling sensitive data, as it ensures that unauthorised modifications to application code are impossible to execute unnoticed.

Challenges of Implementing Confidential Computing in the Real World

Despite its advantages, the adoption of confidential computing is not without challenges. One key barrier is the complexity of integrating TEEs into existing workflows and applications. The leading technology experts at the Eyes-Off Data Summit identified three main implementation challenges and strategies for overcoming them:

1. Performance Overhead and System Compatibility

Traditional TEEs like Intel’s SGX have historically faced limitations due to frequent system calls, which result in performance lags. These bottlenecks are especially challenging for high-frequency transaction environments like finance, where speed is paramount. Innovations have emerged to address these issues, allowing entire virtual machines to run within secure enclaves. This reduces the need for context switching and significantly improves the efficiency of TEEs, making them more compatible with large-scale, high-speed applications.

2. Lifecycle Management and Secure Communication Channels

Managing the lifecycle of secure enclaves is crucial for organisations implementing confidential computing at scale. From creation and attestation to retirement, TEEs require meticulous control over every phase of operation. The challenge lies in integrating TEEs with existing infrastructure and CI/CD pipelines.

Since many organisations rely on automated deployment processes, integrating secure enclaves into these workflows can disrupt established practices. Standard tooling often lacks compatibility with TEEs, making it difficult to automate deployments, updates, and testing. To address these issues, newer confidential computing solutions from companies like Oblivious are focusing on seamless integration with popular CI/CD systems, enabling smoother deployments and reducing the complexity of managing secure applications within existing infrastructure.

3. Specialised Skill Requirements and Organisational Readiness

Confidential computing requires expertise in TEE architecture and secure enclave management. Organisations may need to invest in training or recruit skilled professionals to maintain and troubleshoot these secure environments. To bridge this gap, confidential computing providers are developing more user-friendly tools and frameworks like our OBLV Deploy which doesn’t require your team to have any specialised skills in confidential computing. If your organisation is struggling with any of these challenges, we can help.