研究方法論

Universal Adversarial Attack on Attention and the Resulting Dataset DAmageNet

Authors: Sizhe Chen, Zhengbao He, Chengjin Sun, Jie Yang, Xiaolin Huang | Published: 2020-01-16 | Updated: 2020-10-21
敵対的学習
敵対的攻撃検出
研究方法論

An Adaptive View of Adversarial Robustness from Test-time Smoothing Defense

Authors: Chao Tang, Yifei Fan, Anthony Yezzi | Published: 2019-11-26
ポイズニング
敵対的サンプル
研究方法論

Host-based anomaly detection using Eigentraces feature extraction and one-class classification on system call trace data

Authors: Ehsan Aghaei, Gursel Serpen | Published: 2019-11-25
モデル性能評価
深層学習に基づくIDS
研究方法論

Adversarial Attack with Pattern Replacement

Authors: Ziang Dong, Liang Mao, Shiliang Sun | Published: 2019-11-25
モデル設計
敵対的攻撃手法
研究方法論

Invert and Defend: Model-based Approximate Inversion of Generative Adversarial Networks for Secure Inference

Authors: Wei-An Lin, Yogesh Balaji, Pouya Samangouei, Rama Chellappa | Published: 2019-11-23
モデル設計
敵対的攻撃手法
研究方法論

Universal adversarial examples in speech command classification

Authors: Jon Vadillo, Roberto Santana | Published: 2019-11-22 | Updated: 2021-02-13
敵対的サンプル
敵対的攻撃手法
研究方法論

Attack Agnostic Statistical Method for Adversarial Detection

Authors: Sambuddha Saha, Aashish Kumar, Pratyush Sahay, George Jose, Srinivas Kruthiventi, Harikrishna Muralidhara | Published: 2019-11-22
敵対的サンプル
敵対的攻撃
研究方法論

Optimal Explanations of Linear Models

Authors: Dimitris Bertsimas, Arthur Delarue, Patrick Jaillet, Sebastien Martin | Published: 2019-07-08
モデル選択
研究方法論
解釈可能性の損失

Capacity Bounded Differential Privacy

Authors: Kamalika Chaudhuri, Jacob Imola, Ashwin Machanavajjhala | Published: 2019-07-03
プライバシー保護
情報収集手法
研究方法論

Methodology for the Automated Metadata-Based Classification of Incriminating Digital Forensic Artefacts

Authors: Xiaoyu Du, Mark Scanlon | Published: 2019-07-02
データ抽出と分析
機械学習フレームワーク
研究方法論