Why Your Business Should Use Confidential Computing

Have you ever worried about how securely your company‘s sensitive data is handled as it moves to the cloud? Do compliance requirements keep you up at night wondering if your systems are truly secure? This guide on confidential computing can help put your mind at ease.

I‘m John Smith – an online privacy expert with over 10 years of experience in the cybersecurity industry. I‘ve helped dozens of companies protect their high-value data assets using emerging technologies like confidential computing.

In this beginner‘s guide, I‘ll explain what confidential computing is, how it secures your data, why it‘s valuable for your business, and how you can start leveraging it. Let‘s get started!

An Introduction to Confidential Computing

At a basic level, confidential computing refers to protecting data while it is being actively processed – in memory, rather than just at rest or in transit. This "data in use" protection is achieved through hardware-based secure enclaves and encryption technologies.

Leading technology companies including Microsoft, Google, IBM, and Intel formed the Confidential Computing Consortium to promote security standards that keep data truly private, even in the cloud.

Industry analysts predict the confidential computing market to grow from $160 million in 2020 to over $54 billion by 2026 as threats like cyber attacks, insider data leaks, and non-compliance continue rising rapidly.

What is Confidential Computing and How Does It Work?

Confidential computing leverages two primary mechanisms to keep data private while in use – trusted execution environments (TEEs) and memory encryption:

Trusted Execution Environments

A TEE ensures protected memory regions via:

  • Hardware-level isolation of secure areas called enclaves/containers in CPU and memory.
  • Attestation to validate integrity of code running inside enclaves.
  • Encryption keys managed by TEE hardware to enable secure boot and communication.

Examples of TEE technologies are Intel‘s Software Guard Extensions (SGX) and ARM TrustZone.


Memory encryption augments TEE isolation to keep data secure:

  • Data remains encrypted by memory controllers when stored in RAM/caches.
  • Decryption occurs only within CPU enclaves during actual computation.
  • Prevents unauthorized access to plaintext data outside secure enclave.

Together, these make the TEE an incorruptible "black box" that ensures confidentiality and integrity of data and workloads.

Confidential Computing in Action

Here is the step-by-step data flow:

  1. Application sends encrypted data to TEE enclave memory.
  2. TEE hardware decrypts data inside isolated enclave.
  3. Computation performed on decrypted plaintext data.
  4. Results encrypted before exiting back to application.
  5. Encrypted output returned securely to authorized recipient.

This approach eliminates data exposure risks outside the TEE, reducing attack surfaces.

Why Should Businesses Adopt Confidential Computing?

Research shows over 95% of vulnerabilities stem from software bugs enabling runtime data access, rather than direct cryptographic flaws. Confidential computing defenses mitigate this leading source of compromise.

More specifically, benefits like protecting high-value data, preventing compliance breaches, securely sharing across partners, and reducing costs of data leaks make this a very valuable capability.

Let‘s analyze this in more detail:

1. Protecting Sensitive Data

Over 145 million sensitive records across businesses worldwide were compromised due to data breaches in 2021 alone. The average cost of a corporate data breach now exceeds $4 million.

By keeping data encrypted while in use, confidential computing defends against unauthorized data access attempts, insider threats, malware attacks and implementation exploits targeting vulnerabilities in complex application software stacks.

For example, a major US healthcare network leveraged confidential computing to secure patient medical records and genomic data for cancer research while allowing authorized analytics tools and AI to safely access plaintext data.

2. Achieving Compliance

Over 60% of all data breach incidents involve improper access triggering enforcement action by regulators.

Confidential computing provides evidence of data protection measures being in place through the entire data lifecycle. This facilitates compliance with HIPAA, GDPR, PCI DSS and other data privacy focused regulations.

A global financial services leader utilized confidential computing on AWS to reduce compliance costs by over $250,000 annually while accelerating deployment by 40% over proprietary on-premise hardware security modules.

3. Secure Collaboration

83% of IT leaders report confidential computing enables far greater innovation through secure data sharing with partners.

For instance, confidential computing powers groundbreaking medical research by pharmaceutical companies leveraging shared data analytics across hospitals and academic institutions handling private patient genomic datasets.

The UK NHS has over 50 partnerships with third parties to develop confidential computing tools facilitating such secure data collaboration within the healthcare sector.

4. Limiting Insiders

Insider threats account for over 30% of reported security incidents causing data leaks or IP theft.

Confidential computing isolates plaintext data access to authorized code executed within hardware protected enclaves. This shrinks exposure risk for credentialed users attempting to exceed permissible data use.

A confidential computing strategy allowed a global automotive company to reduce insider threat vulnerabilities by 55% through least-privilege data partitioning.

5. Reducing Breaches

The global WannaCry and NotPetya ransomware attacks encrypted files leading to average business losses of $2.6 million.

By minimizing access to unencrypted data, confidential computing significantly diminishes the impact of such malware, viruses, or general data corruption triggered by malicious actors or software failures.

A retail pharmacy chain mitigated ransomware impact through memory encryption protecting datastores with only 0.5% of files getting compromised versus 18% earlier.

Clearly, the rationale for implementing confidential computing is compelling. Now let‘s look at how organizations are putting this into practice across industries.

Use Cases and Industry Adoption

While confidential computing is broadly applicable across verticals like healthcare, finance, retail, here are some instructive real-world examples of adoption:


The French National Health Service built a confidential computing platform securing healthcare professional data analytics while ensuring compliance with GDPR regulations around patient data privacy.

Meanwhile, a middle east hospital network leverages confidential computing to enable collaboration with global cancer research consortiums through multi-party machine learning on sensitive medical datasets.

Financial Services

15 of the top 20 global financial institutions use confidential computing techniques like homomorphic encryption to share and analyze stock trading algorithms, fraud detection models, and financial risk projections across country offices without exposing proprietary IP or data.

The MAS and IBM have jointly architected blockchain based multi-party computing platforms secured via confidential computing for high value transactions.

Public Sector

Singapore‘s government agencies apply confidential computing to ensure privacy and prevent unauthorized surveillance when operating smart nation infrastructure across domains like transportation, utilities and public safety.

The US Defense Advanced Research Projects Agency (DARPA) looks to enhance data security for classified information sharing across services and external partners through militarized confidential computing cybersecurity technologies.

Cloud Services

Leading cloud providers including Microsoft, Google, Alibaba Cloud, IBM Cloud now offer confidential computing modules and services allowing customers to run sensitive workloads while preventing any access by the host cloud provider itself.

Over 70% of AWS customers already demand these confidential computing features to isolate their tenant workloads, network traffic and stored data from the underlying infrastructure control plane owned by Amazon itself.

Clearly, data security needs across industries are catalyzing innovative deployments of confidential computing worldwide. But some barriers around skills, integration and management complexity persist.

Overcoming Adoption Challenges

Despite strong value propositions, organizations still face some hurdles in adopting confidential computing:

Performance Tradeoffs

The specialized hardware required imposes a 5-15% overhead on processing and latency. Ongoing improvements in CPU design by Intel, AMD and ARM focused on accelerating cryptographic algorithms and trusted execution aim to mitigate this gap.

Meanwhile, intelligent workload scheduling across a mix of confidential and traditional computing capacity can maximize efficiency.

Talent Shortages

59% of CIOs struggle with lack of skills to assess, implement and operate confidential computing technologies within their IT teams. Focused training along with leveraging experienced system integrators and consultants will close this gap over time.

Vendors like Fortanix, Anjuna and Equinix Metal offer managed confidential computing services combining hosting infrastructure with technical expertise necessary for smooth deployments.

Immature Standards

Proprietary vendor approaches to enclave attestation, encryption APIs and backends deter seamless interoperability currently.

However the Confidential Computing Consortium with 100+ industry participants is rapidly developing standards to improve consistency across heterogeneous hardware and platforms.

The adoption roadblocks are temporary. Let‘s now gaze into the future decades where confidential computing becomes ubiquitous!

The Future with Confidential Computing

While yet at an early stage, confidential computing is expected to eventually become as mainstream as technologies like virtualization. IDC estimates over 40% of compute workloads will run via confidential computing modes by 2030 across sectors.

Here are some advances we foresee in 10+ years timeframe:

  • Seamless integration across public/private cloud platforms and on-premise infrastructure.
  • Support emerging quantum-safe cryptographic algorithms resistant to cracking.
  • Enable secure computing with sensitive data in untrusted environments like public blockchains through techniques such as zero-knowledge proofs and homomorphic encryption.
  • Facilitate decentralized identity management without exposing personal user data.
  • Develop specialized IoT hardware like confidential computing capable microcontrollers.

The rapid pace of technology innovation in confidential computing across industry and research bodes well for unlocking a highly secure and transparent digital future across healthcare, finance, commerce and communication platforms!

Wrapping Up

I hope this guide offered you a helpful overview explaining confidential computing, why it matters and how businesses can benefit from adoption. With data vulnerability risks only growing, solutions like confidential computing offer a robust defense-in-depth protection for high value information assets.

Here are my key recommendations as you formulate a data-centric security strategy with confidential computing:

  • Evaluate data protection needs, compliance gaps and sharing use cases to determine applicability.
  • Start small via proofs of concept focused on targeted sensitive workloads.
  • Plan for availability impacts during early testing as standards mature.
  • Architect applications via "cryptographic namespaces" separating encrypted from unencrypted data access.
  • Utilize managed confidential computing services from leading cloud providers to accelerate deployments.

I hope you enjoyed this beginner‘s guide explaining why your business should care about confidential computing! Please share any feedback or questions you may have in the comments section below.