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CHANGELOG.md

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Changelog

Version 1.2.1 (Jul 29, 2024)

Changes:

  • Rename repository from AI-SDC to SACRO-ML (#298)
  • Rename package from aisdc sacroml (#299)

Version 1.2.0 (Jul 11, 2024)

Changes:

  • Add support for scikit-learn MLPClassifier (#276)
  • Use default XGBoost params if not defined in structural attacks (#277)
  • Clean up documentation (#282)
  • Clean up repository and update packaging (#283)
  • Format docstrings (#286)
  • Refactor (#284, #285, #287)
  • Add CLI and tools for generating configs; significant refactor (#291)
  • Add different implementation modes for online and offline LiRA (#281)

Version 1.1.3 (Apr 26, 2024)

Changes:

  • Add built-in support for additional datasets (#257)
  • Remove references to final score in outputs (#259)
  • Update package dependencies: remove support for Python 3.8; add support for Python 3.11 (#262)
  • Fix code coverage reporting (#265)
  • Remove useless pylint suppression pragmas (#269)
  • Fix axis labels in report ROC curve plot (#270)

Version 1.1.2 (Oct 30, 2023)

Changes:

  • Fix a bug related to the rules.json path when running from package (#247)
  • Update user stories (#247)

Version 1.1.1 (Oct 19, 2023)

Changes:

  • Update notebook example paths (#237)
  • Fix AdaBoostClassifier structural attack (#242)
  • Move experiments module and configs to separate repository (#229)

Version 1.1.0 (Oct 11, 2023)

Changes:

  • Add automatic formatting of docstrings (#210)
  • Update user stories (#217)
  • Add module to run experiments with attacks and gather data (#224)
  • Fix bug in report.py: error removing a file that does not exist (#227)
  • Add structural attack for traditional and other risk measures (#232)
  • Fix package installation for Python 3.8, 3.9, 3.10 (#234)

Version 1.0.6 (Jul 21, 2023)

Changes:

  • Update package dependencies (#187)
  • Fix bug when n_dummy_reps=0 in worst case attack (#191)
  • Add ability to save target model and data to target.json (#171, #175, #176, #177)
  • Add safemodel SDC results to target.json and attack_results.json (#180)
  • Add generalisation error to target.json (#183)
  • Refactor attack argument handling (#174)
  • Append attack outputs to a single results file (#173)
  • Attack outputs written to specified folder (#208)
  • Add ability to run membership inference attacks from the command line using config and target files (#182)
  • Add ability to run attribute inference attacks from the command line using config and target files (#188)
  • Add ability to run multiple attacks from a config file (#200)
  • Add user story examples (#194)
  • Improve attack formatter summary generation (#179)
  • Attack formatter moves files generated for release into subfolders (#197)
  • Fix a minor bug in the attack formatter (#204)
  • Improve tests (#196, #199)

Version 1.0.5 (Jun 5, 2023)

Changes:

  • Fix a bug calculating the number of data samples in the Data class (#105)
  • Add a fail-fast mechanism for the worst case attack that enables the number of attack repetitions to terminate early based on a given metric and comparison operator (#105)
  • Change the logging message when attack repetitions are run to 1-10 instead of 0-9 (#105)
  • Add the ability to specify the number of worst case attack dummy repetitions on the command line (#105)
  • Add LIRA fail-fast mechanism (#118)
  • Add the ability to load LIRA attack parameters from a config file (#118)
  • Add the ability to load worst case attack parameters from a config file (#119)
  • Standardise the MIA attack output (#120)
  • Prohibit the use of white space in report file names (#154)
  • Improve the safemodel request release test (#160)
  • Refactor LIRA attack tests (#151)
  • Fix setting the number of LIRA shadow models from a config file (#165)
  • Fix OS system calls relying on calling "python" (#162)
  • Fix invalid command line argument in worst case attack example (#164)
  • Add current output JSON format documentation (#168)
  • Add current attack config format documentation (#168)

Version 1.0.4 (May 5, 2023)

Changes:

  • Fixed SafeRandomForestClassifier "base estimator changed" error (#143)

Version 1.0.3 (May 2, 2023)

Changes:

  • Refactored metrics (#111)
  • Fixed a bug making a report when dummy reps is 0 (#113)
  • Fixed safemodel JSON output (#115)
  • Added a module to produce recommendations from attack JSON output (#116)
  • Disabled non-default report logs (#123)
  • Fixed a minor bug in worst case example (#124)

Version 1.0.2 (Feb 27, 2023)

Changes:

  • Added support for Python 3.8, 3.9 and 3.10 and update requirements.
  • Fixed documentation links to notebooks and added SafeSVC.
  • Added option to include target model error into attacks as a feature.

Version 1.0.1 (Nov 16, 2022)

Changes:

  • Increased test coverage.
  • Packaged for PyPI.

Version 1.0.0 (Sep 14, 2022)

First version.