2.5 KiB
2.5 KiB
Table of Contents
PerfSPEC Learning Phase - ABOUT
Based in PrefSPEC: Performance Profiling-based Proactive Security Policy Enforcement for Containers document presented in [1], this repository contains source files used to generate and process data.
For more info use:
- PrefSPEC main description
- PrefSPEC introduction
- PrefSPEC reference document
- Presentación in Spanish
- How to install
- Autogenerated graph view of actions and events distribution
What is done so far ?
- Good look and feel and interactions among processing, analisys and presentation layers
- Use better software packages management like uv to complement Python pip
- Use an >open and compatible notebook like Marimo to support alternative dataframes engines like Polars rather than Pandas
- Use settings and structures to play with different settinigs and options
- Implement one customized LSTM model within notebooks
- Use of different metrics to apply to the training models with custumezable adjustments and checkpoints
- Use notebooks as python scripts for command-line use cases like collect predictions or automatic train models
- Use Dry to reuse code and centralize common tasks like settings or loading resources. This is main use and existence of lib_perfspec.py
- Splitting basic tasks among several specific notebooks:
- Preprocessing data collection to generate clean and usefull (critical actions) info to train models and ranking prepare_perfspec.py
- Train models to get predictions train_perfspec.py
- Get predictions from existing models run_perfspec.py
- Review and analisys trained models for better results model_perfspec.py