diff --git a/mblearn/attack_model.py b/mblearn/attack_model.py index f01ffc4..60e8e74 100644 --- a/mblearn/attack_model.py +++ b/mblearn/attack_model.py @@ -42,7 +42,7 @@ def __init__(self, target_classes, attack_learner): self._fited = False @staticmethod - def _update_learner_params(learner, learner_params: Dict) -> None: + def _update_learner_params(learner, **learner_params) -> None: # safety check if dict is well formed for k in learner_params.keys(): if not hasattr(learner, k): @@ -50,10 +50,10 @@ def _update_learner_params(learner, learner_params: Dict) -> None: f' an attribute of {learner.__class__}') # update learner params - learner.__dict__.update(learner_params) + learner.__dict__.update(**learner_params) - def fit(self, shadow_data, learner_kwargs: dict) -> None: + def fit(self, shadow_data, **learner_kwargs) -> None: """ Trains `attack_models` with `shadow_data`. Each model is trained with with a subset of the same class of `shadow_data`. @@ -92,7 +92,7 @@ def fit(self, shadow_data, learner_kwargs: dict) -> None: y = membership_label[class_label == i] #update model params - self._update_learner_params(model, learner_kwargs) + self._update_learner_params(model, **learner_kwargs) # train model model.fit(X, y) diff --git a/mblearn/shadow_model.py b/mblearn/shadow_model.py index bb82cfc..8d6ac97 100644 --- a/mblearn/shadow_model.py +++ b/mblearn/shadow_model.py @@ -1,11 +1,16 @@ from typing import List, Tuple, Dict +from copy import copy from tqdm import tqdm_notebook + import numpy as np -from sklearn.model_selection import train_test_split, StratifiedShuffleSplit -from sklearn.base import clone import pandas as pd +from sklearn.model_selection import train_test_split, StratifiedShuffleSplit +from sklearn.base import clone, BaseEstimator + +import tensorflow as tf + import warnings warnings.filterwarnings("ignore") @@ -14,16 +19,11 @@ class ShadowModels: """ Creates a swarm of shadow models and trains them with a split of the synthetic data. - - TODO: - - Run prediction on both training and test splited data - - Label the resulting prediction vector with "in"/"out" - if it was train or test - - drop mic """ - def __init__(self, n_models: int, data: np.ndarray, - target_classes: int, learner): + def __init__(self, X: np.ndarray, y: np.ndarray, + n_models: int, target_classes: int, + learner, **fit_kwargs): """ Creates a swarm of shadow models and trains them with a split of the synthetic data. @@ -54,52 +54,53 @@ def __init__(self, n_models: int, data: np.ndarray, """ self.n_models = n_models - if isinstance(data, pd.DataFrame): - self.data = data.values - else: - self.data = data + self.X = X + if self.X.ndim > 1: + self.X = self.X.reshape(self.X.shape[0],-1) # flatten images or matrices inside 1rst axis + + self.y = y self.target_classes = target_classes - self.splits = self._split_data(self.data, self.n_models) + self.splits = self._split_data(self.X, self.y, self.n_models, self.target_classes) self.learner = learner self.models = self._make_model_list(self.learner, self.n_models) # train models - self.results = self.train_predict_shadows() + self.results = self.train_predict_shadows(**fit_kwargs) @staticmethod - def _split_data(data, n_splits) -> List[np.ndarray]: + def _split_data(X: np.ndarray, + y: np.ndarray, + n_splits: int, + n_classes: int) -> List[np.ndarray]: """ Split manually into n datasets maintaining class proportions - - Suposes class label is at data[:,-1] """ # data = np.hstack((data[0], data[1].reshape(-1, 1))) - X = data - y = data[:, -1] - classes = np.unique(y) - n_classes = len(classes) - - cls_partitions = [] + # X = data + # y = data[:, -1] + classes = range(n_classes) + class_partitions = [] # Split by class - for cl in classes: + for clss in classes: - X_cls = X[y == cl, :] - # y_cls = y[y == cl] + X_cls = X[y == clss] + y_cls = y[y == clss] batch_size = len(X_cls)//n_splits splits = [] for i in range(n_splits): split_X = X_cls[i*batch_size:(i+1)*batch_size, :] - # split_y = y_cls[i*batch_size:(i+1)*batch_size] - splits.append(split_X) - cls_partitions.append(splits) + split_y = y_cls[i*batch_size:(i+1)*batch_size] + splits.append((split_X, split_y)) + class_partitions.append(splits) # ------------------- - # consolidate splits + # consolidate splits into ndarrays # ------------------- + grouped = [] for split in range(n_splits): parts = [] - for part in cls_partitions: + for part in class_partitions: parts.append(part[split]) grouped.append(parts) @@ -114,10 +115,15 @@ def _make_model_list(learner, n) -> List: """ Intances n shadow models, copies of the input parameter learner """ - models = [clone(learner) for _ in range(n)] + if isinstance(learner, tf.keras.models.Model): + models = [copy(learner) for _ in range(n)] + + elif isinstance(learner, BaseEstimator): + models = [clone(learner) for _ in range(n)] + return models - def train_predict_shadows(self): + def train_predict_shadows(self, **fit_kwargs): """ "in" : 1 "out" : 0 @@ -131,7 +137,7 @@ def train_predict_shadows(self): X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.5) - model.fit(X_train, y_train) + model.fit(X_train, y_train, **fit_kwargs) # data IN training y_train = y_train.reshape(-1, 1) predict_in = model.predict_proba(X_train) diff --git a/notebooks/data_synthesis_playground.ipynb b/notebooks/data_synthesis_playground.ipynb index 2d9c2cb..737e351 100644 --- a/notebooks/data_synthesis_playground.ipynb +++ b/notebooks/data_synthesis_playground.ipynb @@ -179,13 +179,13 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 18, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "16226ae9aecd4a64a17e26975521dfe5", + "model_id": "774184e01b3c4300866678b0f194d5b1", "version_major": 2, "version_minor": 0 }, @@ -223,7 +223,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "e0e28d86afbb4a6cbf95625cbd84d764", + "model_id": "a9d23e5c50da42bdbd8c48a439e1fe97", "version_major": 2, "version_minor": 0 }, @@ -261,7 +261,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "374f12f50f0f4512ae51bb2b5b0bdd89", + "model_id": "f04352d1e2f5443d8fe4fb1717ec308e", "version_major": 2, "version_minor": 0 }, @@ -300,18 +300,18 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "array([0.3530678 , 0.50404898, 0.24804805, 0.83584145, 0.90705848,\n", - " 0.19063488, 0.09324932, 0.28178867, 0.19034947, 0.67649903,\n", - " 0.07207215, 0.02897178, 0.90057428])" + "array([0.55795068, 0.81012408, 0.13737383, 0.7644972 , 0.95408134,\n", + " 0.89738274, 0.15180988, 0.52007582, 0.18636001, 0.50824542,\n", + " 0.19594875, 0.19384141, 0.10582045])" ] }, - "execution_count": 15, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" } @@ -322,7 +322,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 11, "metadata": {}, "outputs": [ { @@ -333,7 +333,7 @@ " 0.45528455, 0.97069597, 0.56134094])" ] }, - "execution_count": 16, + "execution_count": 11, "metadata": {}, "output_type": "execute_result" } @@ -344,7 +344,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 12, "metadata": {}, "outputs": [], "source": [ @@ -353,7 +353,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 13, "metadata": {}, "outputs": [], "source": [ @@ -376,7 +376,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 14, "metadata": {}, "outputs": [], "source": [ @@ -393,7 +393,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 15, "metadata": {}, "outputs": [], "source": [ @@ -413,22 +413,22 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 16, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 14, + "execution_count": 16, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": "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\n", + "image/png": "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\n", "text/plain": [ "
" ] diff --git a/notebooks/full_attack.ipynb b/notebooks/full_attack.ipynb deleted file mode 100644 index 59f3771..0000000 --- a/notebooks/full_attack.ipynb +++ /dev/null @@ -1,553 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Attacker model\n", - "\n", - "Here we will put it all togheter using the generated synthetic data from `data_synthesis_playground.ipynb`" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "from mblearn import AttackModels, ShadowModels" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "from sklearn.ensemble import RandomForestClassifier\n", - "from sklearn.datasets import load_wine\n", - "from sklearn.preprocessing import MinMaxScaler\n", - "from sklearn.model_selection import train_test_split\n", - "import pandas as pd\n", - "import numpy as np" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "First we need to make a target model (we will use RandomForest with 100 estimators)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Target model\n", - "\n", - "We are going to use the wine datasetm which have 13 features and 3 classes" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "rf_target = RandomForestClassifier(n_estimators=100)\n", - "data, target = load_wine(return_X_y=True)" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [], - "source": [ - "scaler = MinMaxScaler()\n", - "data_std = scaler.fit_transform(data)\n", - "\n", - "# split to test membership in X_train\n", - "X_train, X_test, y_train, y_test = train_test_split(data_std, target, test_size=0.4)\n", - "\n", - "rf_target.fit(X_train, y_train);" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Shadow model\n", - "\n", - "Now train the Shadow models with synthetic data and the same learner." - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
\n", - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
0123456789101112label
00.6056400.9184870.9052980.2708370.9254690.7983830.8146410.1154320.4941720.5727260.9231590.6031520.8639320
10.8902260.5555330.4402640.5376940.2284970.5154910.6312500.6770990.7843320.1999120.3229020.6307140.9506250
20.5454360.6303460.9888580.3512250.6993220.6370160.8416960.8287620.7439400.4624670.5744510.9122720.5513070
30.9403810.9124750.0085000.1126980.5015840.7072800.8211040.5647980.7441420.3479870.7782790.7367860.5954580
40.7122150.4525270.9421170.3539320.2652240.5364120.7735130.9801100.6547030.7329170.9325850.5844280.4653970
\n", - "
" - ], - "text/plain": [ - " 0 1 2 3 4 5 6 \\\n", - "0 0.605640 0.918487 0.905298 0.270837 0.925469 0.798383 0.814641 \n", - "1 0.890226 0.555533 0.440264 0.537694 0.228497 0.515491 0.631250 \n", - "2 0.545436 0.630346 0.988858 0.351225 0.699322 0.637016 0.841696 \n", - "3 0.940381 0.912475 0.008500 0.112698 0.501584 0.707280 0.821104 \n", - "4 0.712215 0.452527 0.942117 0.353932 0.265224 0.536412 0.773513 \n", - "\n", - " 7 8 9 10 11 12 label \n", - "0 0.115432 0.494172 0.572726 0.923159 0.603152 0.863932 0 \n", - "1 0.677099 0.784332 0.199912 0.322902 0.630714 0.950625 0 \n", - "2 0.828762 0.743940 0.462467 0.574451 0.912272 0.551307 0 \n", - "3 0.564798 0.744142 0.347987 0.778279 0.736786 0.595458 0 \n", - "4 0.980110 0.654703 0.732917 0.932585 0.584428 0.465397 0 " - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "synth_data = pd.read_csv('synthetic_data.csv')\n", - "synth_data.head()" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [], - "source": [ - "rf_shadow = RandomForestClassifier(n_estimators=100)" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "272dd76bd89746b8af36d647a4fe9800", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "HBox(children=(IntProgress(value=1, bar_style='info', max=1), HTML(value='')))" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n" - ] - } - ], - "source": [ - "sh = ShadowModels(5, synth_data, 3, rf_shadow)" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [], - "source": [ - "shadow_data = sh.results" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Attacker" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Now that we have the shadow dataset we can train the attacker model. The attacker learner doesn't need to be the same as the target so pick the one that performs the best.\n", - "\n", - "`AttackModels` trains a model for each original class in shadow data (and in target model) with the in/out of training label as the target label." - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [], - "source": [ - "rf_attack = RandomForestClassifier(n_estimators=100)" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [], - "source": [ - "attacker = AttackModels(target_classes=3, attack_learner=rf_attack)" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [], - "source": [ - "attacker.fit(shadow_data, learner_kwargs={})" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "now lets test with all `X_train` and `X_test`. 50/50 " - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [], - "source": [ - "train_idx = np.random.choice(np.arange(len(X_train)), len(X_test))\n", - "X_train = X_train[train_idx]\n", - "y_train = y_train[train_idx]" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "72 72\n" - ] - } - ], - "source": [ - "print(len(X_train), len(X_test))" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": {}, - "outputs": [], - "source": [ - "X_in = rf_target.predict_proba(X_train)\n", - "res_in = attacker.predict(X_in, y_train, batch=True)" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "metadata": {}, - "outputs": [], - "source": [ - "X_out = rf_target.predict_proba(X_test)\n", - "res_out = attacker.predict(X_out, y_test, batch=True)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Some metrics" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "0.9305555555555556" - ] - }, - "execution_count": 18, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "np.sum(np.argmax(res_in, axis=1)) / len(res_in)" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "0.3055555555555556" - ] - }, - "execution_count": 19, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "1 - np.sum(np.argmax(res_out, axis=1)) / len(res_out)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Precision, Recall and F-1 \n", - "since the class balance is 50/50 a dumb classifier will achieve 0.5 precision, 1 recall and 0.67 f-1" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "metadata": {}, - "outputs": [], - "source": [ - "from sklearn.metrics import precision_score, recall_score, f1_score" - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "metadata": {}, - "outputs": [], - "source": [ - "y_pred = np.concatenate((np.argmax(res_in, axis=1), np.argmax(res_out, axis=1)))\n", - "y_true = np.concatenate((np.ones_like(y_train), np.zeros_like(y_test)))" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "0.5726495726495726" - ] - }, - "execution_count": 22, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "precision_score(y_true, y_pred)" - ] - }, - { - "cell_type": "code", - "execution_count": 23, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "0.9305555555555556" - ] - }, - "execution_count": 23, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "recall_score(y_true, y_pred)" - ] - }, - { - "cell_type": "code", - "execution_count": 24, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "0.708994708994709" - ] - }, - "execution_count": 24, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "f1_score(y_true, y_pred)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Not bad for an out of the box setup" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.7.0" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -}