Continuous Model Validation
As AI becomes increasingly integral to business operations, new safety concerns and security threats emerge at an unprecedented pace—outstripping the capabilities of traditional cybersecurity solutions.
The Stakes are High
According to Cisco’s 2024 AI Readiness Index, only 29% of surveyed organizations feel fully equipped to detect and prevent unauthorized tampering with AI technologies. The stakes are high, with potentially significant repercussions.
Continuous Model Validation
DJ Sampath, Head of AI Software & Platform at Cisco, emphasizes the importance of continuous model validation. "When we talk about model validation, it is not just a one-time thing, right? You’re doing the model validation on a continuous basis. As you see changes happen to the model – if you’re doing any type of fine-tuning, or you discover new attacks that are starting to show up that you need the models to learn from – we’re constantly learning all of that information and revalidating the model to see how these models are behaving under these new attacks that we’ve discovered."
Evolution Brings New Complexities
Frank Dickson, Group VP for Security & Trust at IDC, highlights the evolution of cybersecurity over time. "The first macro trend was that we moved from on-premise to the cloud and that introduced this whole host of new problem statements that we had to address. As applications move from monolithic to microservices, we saw this whole host of new problem sets. AI and the addition of LLMs… same thing, whole host of new problem sets."
Adjusting to the New Normal
Jeetu Patel, Executive VP and Chief Product Officer at Cisco, believes that major advancements in a short period of time always seem revolutionary but quickly feel normal. "The second time, you kind of get used to it. The third time, you start complaining about the seats. We ought to make sure that we as companies get adjusted to that very quickly."
Conclusion
As AI continues to evolve, it is crucial for organizations to prioritize continuous model validation and adjust to the new normal. With new threats and vulnerabilities emerging, it is essential to stay ahead of the curve and ensure the security and integrity of AI models.
FAQs
- What is continuous model validation?
- It is the process of regularly checking and revalidating AI models to ensure they are functioning as intended and are not vulnerable to new attacks.
- What are some common security threats to AI models?
- Some common security threats include prompt injection attacks, jailbreaking, and training data poisoning.
- How can organizations protect themselves from these threats?
- By implementing continuous model validation, using AI-specific security solutions, and staying up-to-date with the latest threat intelligence and research.
