Workload Identification with Physical Side Channels for AI Governance

arXiv:2609.00309 · cs.CR, cs.AI, cs.CY, cs.LG · Submitted 2026-08-31 · Read on arXiv

cs.CR, cs.AI, cs.CY, cs.LG

Submitted: 2026-08-31

Updated: 2026-08-31

Terminology

• Trace — 17× in this paper · explained in 2 episodes
• Fine-Tuning — 8× in this paper · explained in 5 episodes
• Accuracy — 7× in this paper · explained in 1 episode
• Adaptation — 5× in this paper · explained in 1 episode
• Verifier — 3× in this paper · explained in 2 episodes
• Low-Rank Adaptation (LoRA) — 2× in this paper · explained in 9 episodes
• Verification — 2× in this paper · explained in 2 episodes
• Adam — 1× in this paper · explained in 2 episodes
• Calibration — 1× in this paper · explained in 7 episodes
• Cooperation — 1× in this paper · explained in 2 episodes
• F1 Score — 1× in this paper · explained in 3 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Generative AI — 1× in this paper · explained in 2 episodes
• Mixture-of-Experts (MoE) — 1× in this paper · explained in 7 episodes
• Network and Distributed System Security Symposium — 1× in this paper
• Spectral Signature — 1× in this paper · explained in 2 episodes

Sources

• Kraken: Higher-order EM Side-Channel Attacks on DNNs in Near and Far Field
• Expert Selections In MoE Models Reveal (Almost) As Much As Text
• Hardware-Enabled Mechanisms for Verifying Responsible AI Development
• Detecting Hidden ML Training With Zero-Overhead Telemetry
• Open Problems in Technical AI Governance
• What does it take to catch a Chinchilla? Verifying Rules on Large-Scale Neural Network Training via Compute Monitoring
• Measurement of Generative AI Workload Power Profiles for Whole-Facility Data Center Infrastructure Planning

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