Comparing AI Application Security to Traditional Cybersecurity

The new threat landscape of AI upends many long-standing principles of cybersecurity. AI brings fundamentally new threats and vulnerabilities to software which existing tools and processes don’t address.

As AI applications serve more critical functions and handle greater volumes of sensitive data, bad actors and nation states are increasingly motivated to target them. Effective AI security requires a paradigm shift that considers unique risks while leveraging solutions purpose-built to mitigate them.

In this white paper, you’ll learn about AI application security and how it compares to traditional cybersecurity. Topics will include:

• How are AI applications fundamentally different from traditional web applications?
• How do traditional application security concepts like open-source scanning, vulnerability testing, and data loss prevention apply to AI?
• What do purpose-built AI security solutions look like, and how do I find the right one for my needs?