Paper

An AI Security Agent for University ACMIS: Multi-Vector Threat Detection and Automated Response

Unreadunread

AI summary

arXiv:2606. 08270v1 Announce Type: new Abstract: University Academic Management Information Systems (ACMIS) are high-value targets for a wide spectrum of security threats including brute-force login attacks, payment fraud, privilege escalation, insider data theft, and academic integrity violations.

Reading status

Priority

About this paper

Authors: Joseph Walusimbi, Joshua Benjamin Ssentongo
Released: 2026-06-09 (2mo ago)
Topic: Related to current project
Relation to my work: Read next because An AI Security Agent for University ACMIS: Multi-Vector Threat Detection and Automated Response overlaps with clean result "Leakage rate is a usable signal for recovering trigger-shaped phrases on Gaperon-1125-1B without knowing the hidden trigger itself (MODERATE confidence)", 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)". Matching terms: word, under, line, rate, compare, language. Source: arxiv cs.CR (Cryptography and Security).
arXiv: 2606.08270

Ask Claude about this paper

Posts a comment with @claude so the runner spins up a Claude Code session scoped to An AI Security Agent for University ACMIS: Multi-Vector Threat Detection and Automated Response. Replies appear in the conversation below.

Comments

No comments yet.

Related records

No links yet.