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MNIST tutorial: crafting adversarial examples with the Jacobian-based saliency map attack

This tutorial explains how to use CleverHans together with a TensorFlow model to craft adversarial examples, using the Jacobian-based saliency map approach. This attack is described in details by the following paper. We assume basic knowledge of TensorFlow. If you need help getting CleverHans installed before getting started, you may find our MNIST tutorial on the fast gradient sign method to be useful.

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MNIST tutorial: the fast gradient sign method and adversarial training

This tutorial explains how to use CleverHans together with a TensorFlow model to craft adversarial examples, as well as make the model more robust to adversarial examples. We assume basic knowledge of TensorFlow.

Setup

First, make sure that you have TensorFlow

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#/bin/bash
#
# Download toolschains:
# git clone https://android.googlesource.com/platform/prebuilts/gcc/linux-x86/arm/arm-eabi-4.7 toolchain
# git clone https://android.googlesource.com/platform/prebuilts/gcc/linux-x86/aarch64/aarch64-linux-android-4.9 -b  marshmallow-release toolchain64
#
# Instructions to set toolchain for build:
# source setupenv 64

case "$1" in

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tmux cheat sheet

(C-x means ctrl+x, M-x means alt+x)

Prefix key

The default prefix is C-b. If you (or your muscle memory) prefer C-a, you need to add this to ~/.tmux.conf:

remap prefix to Control + a