Cloud Security

Key Topics:
• How AI and automation are reshaping cloud environments
• Balancing efficiency, insights, and new security risks
• Strategies for harnessing tools while managing risk.

Why It Matters:

It matters because the same tools that make cloud systems faster and smarter also create new attack surfaces. AI can streamline defenses, but it can also amplify mistakes or be exploited by attackers. Getting this balance right determines whether organizations gain resilience or inherit new vulnerabilities.

Organizations face shifting threat landscapes, evolving regulations and new architectural paradigms. As the CTO of the Cloud Security Alliance, Daniele Catteddu brings a global vantage point on how enterprises, service providers and regulators are navigating this journey, from assurance frameworks and certifications to emerging practices around AI, Zero Trust and distributed infrastructure. In this fireside chat, we will explore how to build cloud resilience that goes beyond perimeter defense: embedding trust and transparency into supply chains, measuring assurance in third-party services, adapting frameworks for hybrid/multi-cloud ecosystems, and preparing for the next wave of disruptive risks. Attendees will leave with both strategic insight and practical touch points for modern cloud security leadership.

Key Topics:
• Securing who gets in, what they can reach, and how data is protected.
• Envolving approaches to identity management and access control
• Safeguarding sensitive information across distributed systems

Why It Matters:
Keeping control of identities and access is the foundation of cloud security. If you can’t be sure who’s in, what they touch, or how data is handled, everything else falls apart. Strong identity and access practices keep sensitive data safe and trust intact.

In the rapidly evolving world of artificial intelligence, the race to build smarter, more powerful models is intensifying. But as AI systems grow in complexity, so do the risks associated with their development. This session invites attendees to step into the role of a guardian, tasked with securing the environments where these intelligent systems are born and trained.

The journey begins with an exploration of AI/ML Ops—the intricate ecosystem that supports model development and training, version control, testing and validation, and deployment. These foundational processes are not just technical steps; they are the lifeblood of AI, where every decision can have far-reaching security implications. As AI models evolve, the importance of robust monitoring, maintenance, and scalability becomes paramount. Yet, with great power comes great responsibility, and the very tools that enable AI to flourish—like GPUs, data storage, and data pipelines—also introduce new vulnerabilities.

As the session delves deeper, the focus shifts to the security challenges that lurk within these AI training environments. Network security is no longer just about keeping the perimeter safe; it’s about understanding the unique vulnerabilities that can arise when dealing with massive datasets and powerful computational resources. This is where the NIST Secure Software Development Framework (SSDF) comes into play, providing a blueprint for integrating security into every stage of the AI/ML process. By aligning with NIST guidelines, AI practitioners can start building security into their systems from day one, ensuring that their creations are resilient against both current and future threats.

But security isn’t just about defending against known dangers; it’s also about anticipating the unknown. This session will guide attendees through the creation of threat models tailored specifically to AI environments. These models act as strategic roadmaps, helping to identify and mitigate risks before they manifest. In a world where AI systems are increasingly dependent on complex supply chains, securing these pipelines becomes as critical as protecting the models themselves.

The final piece of the puzzle is Identity and Access Management (IAM). In the high-stakes world of AI, controlling who has access to training environments and sensitive data is essential. The session will provide best practices for implementing IAM policies that not only protect these environments but also scale as organizations grow.

“Guardians of the Neural Network: Fortifying AI Training Environments in the ML Ops Era” is more than just a technical discussion—it’s a call to action for those who build, deploy, and manage AI systems. It offers a comprehensive, interconnected approach to security, weaving together the threads of AI/ML Ops into a story of vigilance and innovation. Attendees will leave equipped with the knowledge and tools to protect the next generation of AI, ensuring that as these machines become smarter, they also remain secure.

Key Topics:
• Building adaptable, enduring security frameworks
• Applying layered defenses and resilient architectures:
Practical lessons for sustaining trust in shifting threat lands
• Practical lessons for sustaining trust in shifting threat landscapes

Why It Matters:
This panel examines the design of cloud security frameworks that can withstand disruption and adapt to evolving threats. Speakers will highlight layered defenses, resilient architectures, and real-world lessons that help organizations maintain trust and continuity in a rapidly changing environment.