# DeepDetector

**Repository Path**: fangxud/DeepDetector

## Basic Information

- **Project Name**: DeepDetector
- **Description**: 自适应降噪对抗样本检测
- **Primary Language**: Python
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2025-04-14
- **Last Updated**: 2025-04-14

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# DeepDetector
This repository contains the code for the paper "Detecting Adversarial Image Examples in Deep Networks with Adaptive Noise Reduction". It will reproduce the results reported in the paper.

DeepDetector is a straightforward method for detecting adversarial image examples. The method can effectually detect adversarial examples crafted by [Fast Gradient Sign Method](https://arxiv.org/pdf/1412.6572.pdf), [DeepFool method](http://www.cv-foundation.org/openaccess/content_cvpr_2016/papers/Moosavi-Dezfooli_DeepFool_A_Simple_CVPR_2016_paper.pdf) and [attacks designed by Nicholas Carlini and David Wagner](https://arxiv.org/pdf/1608.04644.pdf). Adversarial examples crafted by other attack techniques may also can be detected by this method.<br>

# Reference
Liang B, Li H, Su M, et al. Detecting Adversarial Image Examples in Deep Networks with Adaptive Noise Reduction[J]. arXiv preprint arXiv:1705.08378, 2017.