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arXiv · 2608.21389

Interrupting the Chain: Human Perception of AI-Generated Disinformation Through a Kill Chain Lens

Alexander Loth·Martin Kappes·Marc-Oliver Pahl
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Abstract

Generative AI enables customized misinformation at scale, yet defenses remain largely reactive. We present empirical findings from a human-subject study (n=504 participants, n=2,438 judgments) in which users classified news fragments by origin (human vs. machine) and veracity (real vs. fake). We organize results using an adapted cybersecurity kill chain as a taxonomy for intervention, mapping perception data onto stages of a cognitive attack lifecycle. Three key findings emerge: (1) a perception-accuracy gap where heightened suspicion does not improve detection; (2) modern LLMs frequently produce human-indistinguishable text; and (3) an asymmetric cognitive fatigue effect where fake-news detection degrades by 10.2 percentage points under sustained exposure while AI-origin detection remains stable. These findings identify candidate intervention points for proactive defense against AI-driven disinformation.

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Alexander Loth, Martin Kappes, Marc-Oliver Pahl. 2026-07-26. Interrupting the Chain: Human Perception of AI-Generated Disinformation Through a Kill Chain Lens. https://arxiv.org/abs/2608.21389

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