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An Approach for Considering Human Factors in Root Cause Analysis of Network Systems
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DOI：10.59277/ROMJIST.2026.1.03.png)
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Abstract
En 中文
Root cause analysis (RCA) has the capability to uncover the underlying reasons for anomalies and offers robust support for network systems recovery. However, one of the most significant challenges in RCA is the difficulty in capturing and analyzing the finegrained human factors that trigger anomalies. To address this issue, this paper presents an approach for correlating fine-grained events with key performance indicators (KPIs). Specifically, in this approach, captured function events, treated as fine-grained human factors, are analyzed with modified Petri Nets to determine the root cause of anomalies. The experimental results demonstrate that the proposed approach is highly effective in tracing fine-grained human factors during RCA. Moreover, the F1-score in anomaly recognition can reach approximately 0.79.
Keywords:
Anomaly KPIs
fine-grained human factors
function event
root cause analysis
Journal
R
IF:
3.9
Papers:
26
Citations:
442
Organization
Cited Papers