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Conference: March 16-19, 2026
Exhibits: March 18-19, 2026
West Hall , Las Vegas Convention CenterLas Vegas, NV

2026 Agenda

Deterministic Network Security in the Age of AI-Driven Threats

Federico Simonetti  (Chief Technology Officer, Xiid)
Location: W220
Date: Thursday, March 19
Time: 10:10 am - 10:40 am
Track: Government
Topics: AI, Cybersecurity, Network Infrastructure
Format: Power Session
Vault Recording: TBD

In the age of AI-driven threats, "probably" isn't good enough for critical infrastructure and sensitive data. As artificial intelligence transforms both cybersecurity defenses and attack methodologies, traditional reactive security models are failing enterprises. With 93% of security leaders expecting daily AI-driven attacks in the coming 12-18 months, organizations need deterministic (i.e. security frameworks that prevent breaches by design rather than hoping to detect them post-compromise. This session explores how to deliver absolute security certainty against AI-enhanced threats.

AI-based network intrusion protection systems are based on the ability to detect a threat while it's already ongoing. AI models can and will make mistakes, introducing an element of uncertainty. An alternative approach is to shift from inexact detection to deterministic prevention through architectural design. This method aims to eliminate entire attack surfaces by principle, not just detect their exploitation after the fact.

Key focus areas include securing critical communications infrastructure against sophisticated nation-state actors leveraging ungated AI models for targeted campaigns, protecting against AI-powered supply chain compromises, and implementing security-by-design principles that eliminate rather than react to threats. Real-world case studies from government and enterprise deployments show measurable risk reduction and operational efficiency gains.

This session addresses the critical gap between current security approaches and emerging AI threat vectors, providing actionable strategies for building resilient infrastructure that remains secure regardless of adversarial AI advancement.

Takeaway

• Discuss the difference between deterministic and probabilistic network security
• Understand why probabilistic AI detection cannot match deterministic prevention against advanced persistent threats
• Learn architectural principles that eliminate attack surfaces rather than expanding security monitoring
• Overview of why quantum-resistant security frameworks are needed to protect against current and future decryption threats