Securing Enterprises in the AI Era: A New Normal
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, with potentially significant repercussions. According to Cisco’s 2024 AI Readiness Index, only 29% of surveyed organisations feel fully equipped to detect and prevent unauthorised tampering with AI technologies.
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 and what advancements in AI mean for the industry. "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. And then as applications move from monolithic to microservices, we saw this whole host of new problem sets."
Adjusting to the New Normal
Jeetu Patel, Executive VP and Chief Product Officer at Cisco, notes that major advancements in a short period of time always seem revolutionary but quickly feel normal. "Waymo is, you know, self-driving cars from Google. You get in, and there’s no one sitting in the car, and it takes you from point A to point B. It feels mind-bendingly amazing, like we are living in the future. The second time, you kind of get used to it. The third time, you start complaining about the seats."
Conclusion
As AI and large language models continue to evolve, it is crucial for enterprises to stay ahead of the curve. Cisco’s AI Defense is a self-optimising solution that uses proprietary machine learning algorithms to identify evolving AI safety and security concerns, informed by threat intelligence from Cisco Talos.
Frequently Asked Questions
Q: What is the current state of AI security in enterprises?
A: The current state of AI security in enterprises is a growing concern, with new threats and vulnerabilities emerging at an unprecedented pace.
Q: What is Cisco’s approach to AI security?
A: Cisco’s approach to AI security is to provide a self-optimising solution that uses proprietary machine learning algorithms to identify evolving AI safety and security concerns, informed by threat intelligence from Cisco Talos.
Q: How can enterprises stay ahead of the curve in AI security?
A: Enterprises can stay ahead of the curve in AI security by implementing solutions like Cisco’s AI Defense, which provides continuous model validation and threat intelligence to help prevent unauthorised tampering with AI technologies.
Tags: ai, ai defense, artificial intelligence, cisco, cyber security, cybersecurity, development, dj sampath, enterprise, frank dickson, idc, infosec, jailbreak, jeetu patel, large language models, llm, models, security, vulnerabilities
