Key takeaways:
- Understanding the AI Development Lifecycle: From opportunity discovery to model monitoring, the whitepaper breaks down each stage and highlights potential security risks.
- Traditional Security vs. AI Security: Discover the similarities and differences in securing traditional systems versus AI, including key areas like governance, threat modeling, and data security.
- AI-Specific Threats: Learn about the unique threats to AI systems, such as adversarial examples, data poisoning, and the potential for AI to be used maliciously.
- Practical Recommendations: Get actionable advice on implementing robust security controls, including data protection, secure development practices, threat detection, and incident response.
This whitepaper is a must-read for:
- Security professionals
- AI developers
- Data scientists
- IT leaders
- Anyone involved in building or deploying AI solutions
