DOI: 10.5281/zenodo.17736479
title: Cloud Supply-Chain Dataset

description: This dataset contains real-time, multi-source cloud supply-chain telemetry collected from a live, production-scale multi-cloud environment spanning August 2021 to September 2025. The data was recorded from distributed compute nodes, CI/CD pipelines, container registries, API gateways, identity providers, and security monitoring subsystems operating across hybrid cloud deployments. The dataset represents authentic operational behaviour, including workload fluctuations, dependency updates, routing shifts, and security-driven events that naturally occur in modern software supply-chain ecosystems.

All telemetry is sampled at a fixed 15-minute interval, ensuring consistent temporal resolution for anomaly detection, provenance validation, and federated learning research. The dataset captures both normal operational patterns and real-world attack scenarios, including data-injection attempts, routing manipulation, API misuse, DoS pressure, credential abuse, and exfiltration behaviour.

The dataset includes the following feature categories:



1. Cloud Infrastructure Metrics





Cloud Provider, Region, Service Type — operational metadata identifying the execution environment.




CPU Usage, Memory Usage, Disk I/O, Network In/Out — continuous measurements reflecting workload intensity, resource stress, and system anomalies.




Baseline Deviation Score — deviation from long-term performance baselines computed inside the monitoring pipeline.





2. Dependency and Software Integrity Indicators





Dependency Depth, Version Mismatch Count — structural and update-related characteristics of software components.




Checksum Deviation, Unsigned Binary Count — integrity and trust indicators relevant to detecting tampering or poisoned dependencies.




Repository Trust Score — confidence signal derived from release history and registry metadata.




External Script Execution — event flag indicating unverified or unusual script activations.





3. Network and API Behaviour





Inbound/Outbound Connection Count — network load and communication patterns.




Failed or Unauthorized API Calls — signs of misuse, credential replay, or enumeration attempts.




Encrypted Traffic Ratio — proportion of encrypted flows over total observed traffic.





4. Access and Identity Signals





Failed Login Attempts, Privilege Escalation Flag, Access Token Reuse — identity and authentication-related indicators used to detect abuse or lateral movement.





5. Process and Execution Activity





Process Creation Count, Dynamic Library Loads, Code Injection Flag — runtime behaviour that reflects execution anomalies or malware-like patterns.




Malicious Signature Match — detection outcomes from integrated security engines.





6. Event Logs and Policy Compliance





Error Log Count, Policy Breach Count, Unauthorized Access Events — system-level and administrative event markers.





7. Threat Intelligence and Incident Indicators





Threat Intel Hits, Security Alerts, Critical Alert Ratio — threat-feed correlation and severity assessment.




Incident Response Time — operational responsiveness under different incident conditions.





8. Temporal and Statistical Properties





Burstiness Index, Change Rate Per Hour — temporal volatility descriptors suited for detecting drift, unusual bursts, or stealthy anomalies.





9. Labels and Target Variables





Attack_Type — one of six real attack categories:Normal Operation, Data Injection, Routing Manipulation, DoS, Credential Abuse, Data Exfiltration.




Attack_Label — binary (0 = normal, 1 = attack).




Severity Score — real-time severity estimation derived from security alerts and behavioral deviation.





Data Integrity and Preprocessing

Before release, the dataset underwent a comprehensive quality-assurance pipeline that included:





Timestamp normalization and deduplication




Removal of corrupted or partially logged records




Standardization of categorical fields




Scaling of continuous features using empirical operating ranges




Preservation of temporal ordering and original heterogeneity