防御効果分析

DeepRobust: A PyTorch Library for Adversarial Attacks and Defenses

Authors: Yaxin Li, Wei Jin, Han Xu, Jiliang Tang | Published: 2020-05-13
アルゴリズム
グラフ機械学習の説明可能性
防御効果分析

Bullseye Polytope: A Scalable Clean-Label Poisoning Attack with Improved Transferability

Authors: Hojjat Aghakhani, Dongyu Meng, Yu-Xiang Wang, Christopher Kruegel, Giovanni Vigna | Published: 2020-05-01 | Updated: 2021-03-14
バックドア攻撃
ポイズニング
防御効果分析

Minority Reports Defense: Defending Against Adversarial Patches

Authors: Michael McCoyd, Won Park, Steven Chen, Neil Shah, Ryan Roggenkemper, Minjune Hwang, Jason Xinyu Liu, David Wagner | Published: 2020-04-28
攻撃検出
敵対的攻撃検出
防御効果分析

A cryptographic approach to black box adversarial machine learning

Authors: Kevin Shi, Daniel Hsu, Allison Bishop | Published: 2019-06-07 | Updated: 2020-02-21
セキュリティテスト
敵対的訓練
防御効果分析

Combatting Adversarial Attacks through Denoising and Dimensionality Reduction: A Cascaded Autoencoder Approach

Authors: Rajeev Sahay, Rehana Mahfuz, Aly El Gamal | Published: 2018-12-07
攻撃手法
敵対的サンプルの検知
防御効果分析

Adversarial Attacks, Regression, and Numerical Stability Regularization

Authors: Andre T. Nguyen, Edward Raff | Published: 2018-12-07
ロバスト回帰
敵対的サンプル
防御効果分析

Enhancing Robustness of Machine Learning Systems via Data Transformations

Authors: Arjun Nitin Bhagoji, Daniel Cullina, Chawin Sitawarin, Prateek Mittal | Published: 2017-04-09 | Updated: 2017-11-29
モデルの頑健性保証
モデル抽出攻撃
防御効果分析