As artificial intelligence (AI) continues to revolutionize industries, it also introduces unprecedented security challenges. From data poisoning to adversarial attacks and unintended biases, the vulnerabilities of AI systems can have far-reaching consequences for organizations and society. This session dives into the critical intersection of AI and cybersecurity, offering actionable insights for developers, data scientists, and security professionals.

In this talk, we’ll explore:

Common security threats in AI systems and their real-world implications.
Best practices for securing data pipelines, model training, and deployment.
Strategies for detecting and mitigating adversarial attacks.
Ethical considerations and how transparency can enhance security.
Whether you’re building AI solutions or securing them, this session equips you with the knowledge and tools needed to navigate the risks and protect the promise of intelligent systems.

Key Takeaways:
Understanding the primary security risks associated with AI models and systems.
Implementing robust techniques to safeguard AI pipelines and infrastructure.
Addressing ethical and regulatory challenges to create resilient, trustworthy AI.
Audience Level:
Intermediate to Advanced (Ideal for developers, security engineers, and AI practitioners with some familiarity with AI systems).