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Wei Ling Neo, a product manager at Fortinet, presented an overview of the company’s evolving strategy to address the challenges posed by quantum computing and the rapid rise of “Shadow AI” within enterprise environments. As the anticipated timeline for Q Day–the point at which quantum computers will be capable of breaking existing encryption standards–continues to shift earlier, moving toward 2029 or 2030, Fortinet has been aggressively updating its FortiOS platform. The company has moved from early implementations of Quantum Key Distribution (QKD) in version 7.2 to robust support for standardized Post-Quantum Cryptography (PQC) algorithms, such as ML-KEM and ML-DSA, in its latest 8.0 release.
The technical implementation of these security measures focuses on securing the “plumbing” of the network, particularly IPsec VPN tunnels, which are critical for enterprise connectivity. Neo explained that Fortinet leverages software-based implementations for the key exchange mechanisms to allow for flexibility and stacking of algorithms, which is essential for protecting against potential vulnerabilities in newer, less-tested standards. While the initial key exchange phase sees some performance impact during tunnel setup, bulk encryption and decryption tasks remain offloaded to Fortinet’s proprietary ASICs, ensuring that overall network performance remains high even as organizations transition to quantum-safe protocols.
Beyond quantum security, the presentation addressed the burgeoning crisis of Shadow AI, where unauthorized AI agents and Large Language Models (LLMs) operate within corporate networks, creating significant data leakage and compliance risks, especially under frameworks like the EU AI Act. Fortinet has expanded its visibility capabilities to monitor agent-to-agent (A2A) communications and Model Context Protocol (MCP) servers, allowing security teams to identify, audit, and sanction or block specific AI tools used by employees. By correlating user information with these AI functions, Fortinet aims to provide organizations with the granular reporting and control necessary to manage AI adoption without sacrificing security or productivity.
Personnel: Wei Ling Neo
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