Back to Blogs
CONTENT
This is some text inside of a div block.
Subscribe to our newsletter
Read about our privacy policy.
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.
Industry Trends

Top 5 AI Security Trends Discussed at the Confidential Computing Summit 2024

Published on
June 13, 2024
4 min read

The 2-day conference featured discussions with the smartest minds in confidential computing and privacy-preserving (generative) AI. 

2024 CoCO Summit


In June, I had the pleasure to both attend and speak at the 2024 CoCo Summit in San Franciso. My talk entitled, “Strategies for Effectively Deploying Trustworthy Generative AI Solutions”, was a bit generalized for this audience, as confidential computing solves only one aspect of LLM security, specifically on deployment. 

Nonetheless, I received great feedback on my talk from the audience members, namely how impressed they were with the comprehensiveness of the Enkrypt AI platform. They appreciated its benchmarked and dynamic Red Teaming, Alignment, Guardrails, and continuous Monitoring capabilities. All of which can be done simultaneously in the platform. 

We are proud of building a product that can (among other things):

  1. Detect both security risks (jailbreak, malware, leakage) and model risks (toxicity, bias and hallucinations), and 
  2. Evaluate AI systems against operational and reputational risks throughout development and deployment.

The rest of the conference was filled with presentations from industry luminaries representing Microsoft, Nvidia, Google, and others. 

Top 5 AI Security Trends


Here are the top trends I came away with after digesting the jam-packed content:

  1. Internal threat actors are increasing, so protecting LLM IP is becoming critical. And in some cases, of national security importance. Jason Clinton, CISO, at Anthropic essentially made this point in his presentation.

  2. The technology for confidential computing for Generative AI is not yet mature – confidential GPUs are a year away.

  3. Despite their infancy, use cases for confidential computing are starting to pick up steam. One example is to port the workloads (AI training, data processing) into confidential computing. 
  1. Challenges abound at the CPU-GPU communication level when it comes to confidentiality.

  2. There is an obvious need to provide responsible and secure Generative AI. Threat actors know AI applications are currently an easy and profit-rich target to exploit. 

We look forward to attending next year’s event, as interest will only grow in this industry. 

Meet the Writer
Prashanth H
Latest posts

More articles

Industry Trends

Small Models, Big Problems: Why Your AI Agents Might Be Sitting Ducks

Small language models promise cheaper, faster AI agents, but their weak safety alignment makes them vulnerable to real-world attacks. Learn why SLM security flaws put sensitive data and systems at risk — and what teams must do to deploy them responsibly.
Read post
Industry Trends

Surfing in the dark — Hidden Dangers Lurking on Every Web Page

AI agents like ChatGPT and Comet automate workflows, but they’re vulnerable to indirect prompt injection—malicious hidden instructions in webpages that hijack user intent. Learn how these attacks work, real-world demos of email theft and biased recommendations, and best practices to secure autonomous agents against evolving threats.
Read post
EnkryptAI

Enkrypt AI Recognized as a Representative Provider in Gartner’s MCP Gateways Research

Enkrypt AI is named a Representative Provider in Gartner’s Innovation Insight for MCP Gateways, Sept 2025 — highlighting our commitment to secure, scalable enterprise AI adoption with governance, visibility, and cost efficiency.
Read post