arXiv：cs.AI· Alexander Loth, Martin Kappes, Marc-Oliver Pahl·· 4 小时前AI 评分39
用杀伤链视角研究人类对 AI 生成虚假信息的感知
Interrupting the Chain: Human Perception of AI-Generated Disinformation Through a Kill Chain Lens
AI 导读
一项 504 名参与者、2438 次判断的人类受试研究，用改编自网络安全的杀伤链框架映射 AI 虚假信息的认知攻击生命周期。结果显示存在感知准确率缺口：怀疑度升高并未提升检测能力；现代 LLM 生成的文本常与人类写作难以区分；持续接触下假新闻检测率下降 10.2 个百分点，而 AI 来源识别保持稳定。
正文
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.
| Comments: | Camera-ready version. 10 pages, 3 figures, 2 tables |
| Subjects: | Computers and Society (cs.CY); Artificial Intelligence (cs.AI); Cryptography and Security (cs.CR) |
| ACM classes: | K.4.2; K.6.5; H.1.2; I.2.7 |
| Cite as: | arXiv:2608.21389 [cs.CY] |
| (or arXiv:2608.21389v2 [cs.CY] for this version) | |
| https://doi.org/10.48550/arXiv.2608.21389 arXiv-issued DOI via DataCite |
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| Journal reference: | INFORMATIK 2026, LNI P-384, pp. 321-330 |
| Related DOI: | https://doi.org/10.18420/inf2026_22
DOI(s) linking to related resources |
Submission history
From: Alexander Loth [view email]
[v1]
Sun, 26 Jul 2026 15:40:41 UTC (60 KB)
[v2]
Fri, 2 Oct 2026 06:06:46 UTC (50 KB)
来源：arXiv：cs.AI · arxiv.org