Story · Semantic Scholar
When Cost Objectives Delete Capability: Accuracy-Constrained Tool Selection for Multi-Component Intrusion Detection in IoT Networks (Semantic Scholar)
paper · Story page
Train a tool-selection router purely against cost and, when the informative tools are the expensive ones, it drops the very detectors the system exists to run: attack attribution collapsed on both datasets while the attack-versus-normal metric stayed high. The proposed fix is a mandatory core of class-discriminative tools that cost optimization can't touch.
In plain words
- Researchers found that choosing security checks only by price can remove the checks that identify specific attacks.
- The problem appears when the most useful checks are also the most expensive.
- A broad attack-versus-normal score can stay high even when the system fails to identify most attack families.
- The proposed fix keeps essential identifying checks mandatory, while cost savings apply only to optional checks.
- This matters for network defenders because a cheap system can look accurate while giving nearly useless attack details.
Appeared in
- Google's Mantis bug-fixing harness, and privilege escalation in 12 agent harnesses
Sep 03, 2026 · in the sections
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