Metadata-Version: 2.4
Name: sfalearn
Version: 0.0.10
Summary: Automata Learning
Home-page: https://github.com/GeorgeArgyros/sfalearn
Download-URL: https://github.com/GeorgeArgyros/sfalearn/tarball/master
Author: George Argyros, Ioannis Stais
Author-email: ioannis.stais@gmail.com
Platform: Any
Classifier: Development Status :: 3 - Alpha
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
Classifier: Intended Audience :: Developers
Classifier: Environment :: Console
License-File: LICENSE
Requires-Dist: symautomata>=0.0.12
Dynamic: author
Dynamic: author-email
Dynamic: classifier
Dynamic: description
Dynamic: download-url
Dynamic: home-page
Dynamic: license-file
Dynamic: platform
Dynamic: requires-dist
Dynamic: summary

# sfalearn
Automata Learning classes

A python framework for working with Learning algorithms in Automata.  
This framework is part of the [lightbulb-framework](https://github.com/lightbulb-framework/lightbulb-framework).

## Changelog

0.0.10: Updated version of symautomata (0.0.12) in installation requirements.  

## Contributors

* George Argyros
* Ioannis Stais
* Suman Jana
* Angelos D. Keromytis
* Aggelos Kiayias

## References

* *G. Argyros, I. Stais, S. Jana, A. D. Keromytis, and A. Kiayias. 2016. SFADiff: Automated Evasion Attacks and Fingerprinting Using Black-box Differential Automata Learning. In Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security (CCS '16). ACM, New York, NY, USA, 1690-1701. doi: 10.1145/2976749.2978383*
* *G. Argyros, I. Stais, A. Kiayias and A. D. Keromytis, "Back in Black: Towards Formal, Black Box Analysis of Sanitizers and Filters," 2016 IEEE Symposium on Security and Privacy (SP), San Jose, CA, 2016, pp. 91-109. doi: 10.1109/SP.2016.14*

## Acknowledgements

This research was partly supported by ERC project CODAMODA, #259152.


## License

MIT License as described in LICENSE file
