Zero Trust becomes the foundation of cyber security (www.militaryaerospace.com)

As AI-driven systems face increasing threats—data poisoning, model corruption, opaque “black box” behavior, and adversaries using AI to automate reconnaissance and exploits—Zero Trust and trusted computing are being positioned as the new foundations of cyber security. The shift is significant for the AI/ML community because it reframes risk management from software-only defenses to hardware-enforced integrity: protecting training data and model supply chains, ensuring auditable decision paths where human oversight matters, and blocking automated adversarial pipelines before they can corrupt deployed systems. Vendors cited in the story highlight concrete implementations: Pixus’s SHM300 Tier‑3 SOSA-aligned chassis manager uses Microchip PolarFire FPGAs for stronger encryption/networking, a full Linux stack for complete TCP/IP support, a mezzanine design, RESTful management, and optional fiber Ethernet to reduce eavesdropping. General Micro Systems emphasizes hardware-first controls—zeroization buttons, anti-tamper sensors, and daisy‑chained “Intruder” cables—to physically brick compromised units. Green Hills advocates pairing hardware data diodes (one‑way optical isolation) with software data guards for adaptable content inspection, while tactical cross-domain solutions (e.g., Collins Aerospace’s TCTS II using INTEGRITY‑178 tuMP RTOS) show how certified hardware/software stacks can enforce multi‑level security in deployed systems. For AI/ML practitioners, these trends underscore the need for hardware roots-of-trust, secure data pipelines, and cross-domain architectures to harden model training, deployment, and lifecycle governance.