- Updated to python3.7
- Updated models
- Updated tensorflow to 1.14.0
- Updated pytest to 5.0.1
- Updated models and included printers
- Renamed PoseidonML to NetworkML
- Updated pytest to 4.6.3
- Updated numpy to 1.16.3
- Updated pytest-cov to 2.7.1
- Updated pytest to 4.5.0
- Reduce places that Tensorflow is imported
- Made it possible to run classifications on CPUs that don't support AVX
- Updated Tensorflow imports for new deprecations
- Updated pika to 1.0.1
- Removed a bunch of duplicated code to keep the code base cleaner
- Added a bunch of tests to get coverage up to 90%
- Updated pytest to 4.4.1
- Removed the use of md5 and replaced it with sha224
- Major rewrite and restructuring of the code base, but same functionality
- Changed the default for Rabbit to not be used
- Changed the environment variable for Rabbit from SKIP_RABBIT to RABBIT
- Improved logging output for summarizing evaluation results of multiple PCAPs
- Updated versions of pika, pytest, redis, and scikit-learn
- Fixed a bug that was preventing training the SoSModel
- Added some more test coverage
- Updated the trained models and labels
- Updated tensorflow from 1.12.0 to 1.13.1.
- Updated numpy from 1.16.1 to 1.16.2.
- Miscellaneous error checking and spacing corrections.
- Updated pytest to 4.3.0 from 4.2.0.
- Cleaned up some code issues as pointed out by Codacy.
- Minor miscellaneous bugfixes to support running training natively.
- Provided a way to run DeviceClassifier training and testing scripts from command line.
- Cleaned up some unused code and consolidated common operations into utils and model class.
- Fixed issue where Makefile built the OneLayer training container when building the test one.
- Updated redis to 3.1.0
- Updated numpy to 1.16.1
- Updated numpy to 1.16.0
- Updated pika to 0.13.0
- Included a conda yml file for a standalone/dev environment, and new Makefile options to build it.
- models have been retrained to fix a warning about invalid results when evaluating a pcap
- some unused code and module has been removed
- upgraded pytest to 4.1.0 and pytest-cov to 2.6.1
- upgraded scikit-learn to 0.20.2
- removed scipy
- cleaned up requirements.txt and setup.py
- fixed issue where redis was throwing error when saving decisions
- fixed error in eval_onelayer that was using nonexistent key
- Make train/eval/test process consistent for all models
- Fixed path error specific to python 3.5 that occurred when processing PCAP files
- PCAP directories can now be used when running model evals
- upgraded pytest to 4.0.2
- upgraded scikit-learn to 0.20.1
- improved README documentation
- upgraded redis to 3.0.1
- added pcap directory support
- re-enabled the behavior model
- includes the trained behavior model
- fixed hardcoded onelayer pickle file in randomforest
- fixed missing labels
- simplified rabbit connection
- replaced deprecated randomized logistic regression with random forest
- upgraded pytest to 3.9.1
- fixed a NoneType error when multiplying
- fixed an issue where the config file wasn't being read properly
- abstracted away the code to read the config file into one place
- lots of cleanup of duplicated code
- upgraded tensorflow to 1.11.0
- upgraded scikit-learn to 0.20.0
- updated the model
- moved a bunch of duplicated code into common utils
- fixed issue where results were not getting sent to rabbitmq or stored in redis
- cleaned up cruft in OneLayer Eval
- moved OneLayer Eval code into a class to reduce duplication
- upgraded pytest to 3.8.0
- upgraded pytest-cov to 2.6.0
- upgraded tensorflow to 1.10.1
- made all print statements logger statements
- sends messages to rabbitmq now even if not enough sessions
- stores normal/abnormal results in redis now
- fixed performance issue where evaluation would take a long time
- updated the model
- upgraded pytest to 3.7.2
- upgraded numpy to 1.15.1
- updated model
- upgraded pytest to 3.7.1
- upgraded scikit-learn to 0.19.2
- linting
- fixes pairs issue when checking private addresses
- fixes the models path for running in a container
- improve dockerfile builds
- upgraded pika to 0.12.0
- upgraded scipy to 1.1.0
- upgraded numpy to 1.14.5
- upgraded tensorflow to 1.9.0
- fixed vent template
- added some initial tests
- re-trained the onelayer model with improved accuracy
- reduced the number of labels for onelayer to 6
- improvements for developing on poseidonml
- initial utility release