arXiv cs.AI· Chiara Bonfanti, Cataldo Basile·· 9 天前AI 评分22
GROB：面向候选智能体活动的公开痕迹调查多智能体架构
GROB: A Multi-Agent Architecture for Public-Trace Investigation of Candidate Agentic Activity
AI 导读
GROB 是一个多智能体架构，可在无法获取特权遥测数据时，通过公开互联网痕迹调查候选自主智能体活动，并以受控只读方式采集公开痕迹、保留部分观测供后续解析。在冻结的 2026 年 9 月语料中，9 月 9 日捕获的 Census 标识符后被公开修订记录解析为 6 月 16-17 日的具体 Census 请求。结果表明稀疏公开痕迹在意义尚未明确前仍可能有用，但仅凭公开痕迹无法确立组织归属。
正文 · 原文
Abstract:We present GROB, a multi-agent architecture for investigating candidate autonomous-agent activity through public Internet traces when privileged telemetry is unavailable. The system performs controlled, read-only collection of public traces and preserves selected observations for later resolution. In a frozen September 2026 corpus, several collected traces became more informative as additional public evidence emerged. The strongest result concerns Census-labelled identifiers captured on 9 September. Public revision records later resolved these identifiers to specific Census requests from 16 - 17 June. Other results show weaker links between traces collected by GROB and evidence reconstructed or reported later. These links vary in strength, and only some can be tied to specific public records. The results show that sparse public traces can remain useful even before their significance is fully understood. Such evidence can support later reconstruction, but public traces alone do not establish organizational attribution. Execution identity presents a separate problem, as continuity of agent identity remains an active research question for autonomous language-model agents.
| Subjects: | Cryptography and Security (cs.CR); Artificial Intelligence (cs.AI) |
| Cite as: | arXiv:2610.11467 [cs.CR] |
| (or arXiv:2610.11467v1 [cs.CR] for this version) | |
| https://doi.org/10.48550/arXiv.2610.11467 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Chiara Bonfanti [view email]
[v1]
Thu, 8 Oct 2026 08:17:45 UTC (6,190 KB)
来源：arXiv cs.AI · arxiv.org