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Characterizing AI-Assisted Bot Traffic in Darknet Data: Implications for ICS and IIoT Security

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arXiv:2605. 14209v1 Announce Type: new Abstract: The rise of automated scanning tools and AI assisted reconnaissance agents has significantly altered internet background traffic patterns, threatening the baseline assumptions underlying intrusion detection systems (IDS) deployed in critical infrastructure networks.

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Authors: Alex Carbajal, Caleb Faultersack, Jonahtan Vasquez, Shereen Ismail, Asma Jodeiri Akbarfam
Released: 2026-05-15 (3mo ago)
Topic: Related to current project
Relation to my work: Read next because Characterizing AI-Assisted Bot Traffic in Darknet Data: Implications for ICS and IIoT Security overlaps with clean result "Language-mismatch LoRA SFT on Qwen2.5-7B leaks the trained completion language into bystander directives the model was never trained on, absent under same-language SFT (LOW confidence)", clean result "The marker is a representational handle, not a behavioural one — sharing it between a villain persona and the assistant transfers no misalignment (HIGH confidence)", experiment "#351 follow-up: broader-vocab position-0 sweep at T=1.0 + position-1 suffix isolation". Matching terms: under, line, rate. Source: arxiv cs.CR (Cryptography and Security).
arXiv: 2605.14209

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