Tagged:
adversarial-examples4 posts
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Sponge Examples: Energy and Latency Attacks on Neural Networks
Adversarial inputs that don't fool a model's outputs — they exhaust its compute. Sponge examples maximize inference energy and latency, enabling DoS attacks that bypass rate limits, drain edge-device batteries, and degrade shared inference infrastructure. What they are, how they work, and how to defend against them.
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Voice AI Security: Adversarial Audio, Ultrasonic Injection, and Attacks on Speech-Enabled AI Agents
Voice-enabled AI agents inherit a distinct attack surface that text-focused security misses entirely. Adversarial audio perturbations fool ASR pipelines invisibly, ultrasonic commands exploit microphone analog front-ends, and voice authentication breaks when attackers control TTS. Here's the threat model practitioners need.
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AI in Critical Infrastructure: Attack Surfaces in Industrial Control Systems and Smart Grids
How AI integration into power grids, water treatment, manufacturing, and transportation creates novel attack surfaces distinct from traditional ICS/SCADA threats — sensor spoofing against ML anomaly detectors, adversarial attacks on predictive maintenance, model poisoning in federated industrial AI, and mitigations specific to OT environments.
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Adversarial Examples: The Foundational ML Attack That Still Breaks AI Systems in Production
Imperceptible perturbations that flip neural network classifications — from FGSM and PGD to physical-world stop-sign attacks and LLM adversarial suffixes. What adversarial examples are, why gradient-based attacks work, how defenses hold up, and what this means for production AI systems today.