December 6, 2023 at 05:27AM
Organizations must prioritize securing critical data and IT infrastructure against a growing threat landscape and stringent regulations. Intel’s confidential computing, featuring in their 4th Generation Xeon processors, offers encryption-based protection for AI-powered applications, ensuring data security in storage, transit, and processing, while enabling regulatory compliance.
Meeting Takeaways:
1. Prioritization: Organizations must prioritize the protection of mission-critical data, applications, and workloads to avoid potential disasters due to the broadening threat landscape.
2. Dependence on IT Infrastructure: The high levels of reliability, availability, performance, and security are critical since any disruptions can have serious consequences for businesses, their customers, and society.
3. Regulatory Concerns: The expanding regulatory framework for managing sensitive data is intensifying, with notable sanctions existing for non-compliance.
4. Protection from Cyberattacks: The protection against cyberattacks and data loss, especially for sensitive and personal data processed by enterprise applications, is essential. It necessitates a proactive approach to implement security measures across an organization’s technology stack.
5. Impact of AI: As AI becomes increasingly important in business, protecting the data that AIs use is crucial, given that AI systems often handle sensitive information that could be exploited.
6. Need for Secure AI Data: A balance must be struck between securing AI data and allowing AI models the freedom to operate effectively.
7. Confidential Computing: Intel suggests confidential computing as a solution, using encryption to protect data in transit and ensure that only authorized entities have access.
8. Intel’s 4th Generation Xeon Processors: These processors have security features designed to prevent data theft and built-in accelerators that enhance AI workload performance.
9. Innovations in Processor Security: Two key Intel technologies include Intel Software Guard Extensions (SGX) for protecting data in use and Intel Trust Domain Extensions (TDX) for isolating virtual machines.
10. Additional Security Layers: Intel’s suite of tools such as remote attestation and Trust Authority Service offer organizational assurances against data breaches at the system level.
11. Federated Learning: As an AI/ML application protection strategy, federated learning enables collaborative data sharing for insights without compromising sensitive information.
12. Architecture Importance: A secure and trusted architecture is vital for companies to deploy AI-powered applications and workloads with confidence, abiding by security and compliance mandates.
Sponsorship Note: The meeting content was sponsored by Intel, and the attendees are urged to acknowledge the performance variables, security requirements, and that results may vary based on different configurations and activation of hardware, software, or services.
Performance Disclaimer: Intel provided a disclaimer regarding performance variability, configuration, and updates, with a reminder to check backup for configuration details and an advisory that no product guarantees absolute security.