Papers for

educational it administrators

Papers whose findings have a practical use for this group, as judged from the abstract. Open a paper to read what it means in practice.

Incident response subsystem controls alerts with rules and local ai

Design and Evaluation of a Controlled Post-Alert Incident Orchestration and Response Subsystem Using a Rule Engine and a Local Large Language Model

Abstract: This paper presents a controlled post-alert incident orchestration and response subsystem for educational information systems. The architecture separates deterministic classification, contextual analysis, human approval, and technical execution. A Rule Engine determines severity and selects the playbook, while Static RAG and a local large language model provide advisory content under Validator, Guardrail, Output Sanitizer, and Safe Fallback controls. Experiments begin after simulated alerts are stored in Elasticsearch. The Rule Engine matched the predefined routing matrix in all 30 boundary cases. The Durable Queue completed 100 events without duplicate tasks, new failed tasks, or unintended firewall rules. An eight-alert contention experiment preserved the configured limit of one active model request, and 30 sequential measurements showed an overall mean post-alert processing time of approximately 33 seconds. The results demonstrate functional correctness, traceability, controlled recovery, and bounded model integration within the evaluated laboratory scope.

Tue 22 SeptCryptography and SecuritySoftware Engineering

The gist

Handling alerts after security or system incidents can be complicated and slow. The authors present a system that uses clear rules and a local AI model to decide how serious an alert is and suggest what to do next, while keeping humans in control. Their tests showed the system works correctly, keeps track of actions, can recover from problems, and keeps AI use predictable. This helps manage alerts in education IT systems more efficiently.

Open → 2609.26316v1