IT Configuration Drift Anomaly Detection Benchmark

#Time-series anomaly detection #Configuration drift identification #Anomaly interval localization #Model evaluation #IT configuration management #Baseline auditing #Change oversight #Operational state monitoring

5560
0.4GB
JSON
CATL
MOBIUSI INC

Updated:2026-11-04

AI Analysis & Value Prop

This benchmark contains periodic multivariate observations of IT configuration items relative to their baselines, covering details such as versions, policy compliance, and change status. It labels whether anomalous drift occurred, along with its category, severity, and time interval. The data supports evaluation of continuous configuration monitoring, baseline deviation detection, and anomaly localization, and is suited to baseline audits, change oversight, and anomaly detection validation.

Dataset Insights

Sample Examples

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Technical Specifications

Field	Type	Description
file_name	string	File name
drift_annotation	object	Benchmark labels indicating whether anomalous drift occurred and, if applicable, its category, severity, and time interval.
baseline_comparison	object	Comparison features computed from the observed configuration state and its baseline.
configuration_observation	object	A raw snapshot of a configuration item, including its observed state relative to the baseline.

Compliance Statement

Authorization Type	Proprietary - Commercial AI Training License (No Redistribution)
Commercial Use	Requires exclusive subscription or authorization contract (monthly or per-invocation charging)
Privacy and Anonymization	No PII, no real company names, simulated scenarios follow industry standards
Compliance System	Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs

Frequently Asked Questions

What does the dataset contain?: It contains periodic observations of configuration items relative to their baselines, with labels indicating whether drift occurred and specifying its category, severity, and time interval. It also includes comparison features derived from the observed state and its baseline.

Which capabilities can this benchmark evaluate?: It can evaluate continuous IT configuration monitoring, anomalous drift identification, anomaly interval localization, and baseline deviation detection. It can also help validate change oversight workflows in configuration management.

What are the dataset size and file format?: The available information does not specify the sample count, time span, or file format. The schema covers configuration observations, drift annotations, and baseline comparisons; consult the product page or delivery notes for exact size and format.

How can I obtain the data, and what are the licensing terms?: Check the dataset product page for access instructions and license terms. Before use, verify the permitted scope, commercial use restrictions, and redistribution requirements, and handle configuration and asset information according to your compliance policies.

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Cite this Work

@dataset{Mobiusi2026,
  title={IT Configuration Drift Anomaly Detection Benchmark},
  author={MOBIUSI INC},
  year={2026},
  url={https://www.mobiusi.com/datasets/ba77b711d53ab06658572e7e94cca8bc},
  urldate={2026-10-26},
  keywords={IT configuration drift dataset,configuration anomaly detection,configuration baseline auditing,IT state monitoring,multivariate time series,change oversight,drift interval labels,anomaly detection benchmark},
  version={1.0}
}

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