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+# PerfSPEC Learning Phase
+
+Based in [PrefSPEC: Performance Profiling-based Proactive Security Policy Enforcement for Containers](https://ieeexplore.ieee.org/document/10577533) document presented in [1], thir repository contains source files used to generate and process data.
+
+[PrefSPEC document](PerfSPEC.pdf)
+
+[Presentación in Spanish](presentacion.pdf)
+
+<div style="margin: auto">
+ <a target="_blank" href="perfspec-learning/src/branch/main/presentacion.pdf"><img src="imgs/prefSPEC-learning.png" width="800"></a>
+</div>
+
+__PerfSPEC__ has three phases:
+
+- Ranking
+- Learning
+- Runtime
+
+This repository is focused in __Learning__ phase with attention on:
+
+- Event logs info load and process
+- Predictive learning model 
+
+> Note: It is considered that __event data collection__ in `raw-audit-logs.log.gz` are realistic and representative to simulate
+administrative operations.
+
+## Files
+
+- `raw-audit-logs.log` contains raw Kubernetes audit logs collected using the `audit-policy.yaml` audit policy.
+
+Tools are distributed in directories:
+
+- [Collect](collect)
+- [Process](process)
+- [Learning](learning)
+
+As some tasks can be used in [Python](https://python.org) or [Rust](https://www.rust-lang.org/) there are directories for each programming languge inside directories tasks.  
+
+Each `task/programming-language` may have a __data__ directory where processing output files is generated. 
+
+### Collect data
+
+If you wish to [collect](collect) your own dataset, there are several source files that might help:
+
+- `collect/collect.py` is a script to trigger the installation and uninstallation of public Helm repositories.
+- `collect/helm-charts.json` is a backup of Helm charts used at the time of the collection.
+
+### Process data 
+
+
+### Learning
+
+
+
+## Reference
+
+[1]: [H. Kermabon-Bobinnec et al., "PerfSPEC: Performance Profiling-based Proactive Security Policy Enforcement for Containers," in IEEE Transactions on Dependable and Secure Computing, doi: 10.1109/TDSC.2024.3420712.](https://ieeexplore.ieee.org/document/10577533)