文献データベース

Machine Learning Models that Remember Too Much

Authors: Congzheng Song, Thomas Ristenpart, Vitaly Shmatikov | Published: 2017-09-22
プライバシー保護メカニズム
プライバシー漏洩
モデル抽出攻撃

Automatic Detection of Malware-Generated Domains with Recurrent Neural Models

Authors: Pierre Lison, Vasileios Mavroeidis | Published: 2017-09-20
マルウェア検出
モデル性能評価
機械学習技術

Practical Machine Learning for Cloud Intrusion Detection: Challenges and the Way Forward

Authors: Ram Shankar Siva Kumar, Andrew Wicker, Matt Swann | Published: 2017-09-20
モデル抽出攻撃
攻撃検出
機械学習技術

Mitigating Evasion Attacks to Deep Neural Networks via Region-based Classification

Authors: Xiaoyu Cao, Neil Zhenqiang Gong | Published: 2017-09-17 | Updated: 2019-12-31
モデルの頑健性保証
対抗的学習
敵対的サンプルの検知

Detection of Unauthorized IoT Devices Using Machine Learning Techniques

Authors: Yair Meidan, Michael Bohadana, Asaf Shabtai, Martin Ochoa, Nils Ole Tippenhauer, Juan Davis Guarnizo, Yuval Elovici | Published: 2017-09-14
バックドアモデルの検知
モデル性能評価
攻撃検出

Models and Framework for Adversarial Attacks on Complex Adaptive Systems

Authors: Vahid Behzadan, Arslan Munir | Published: 2017-09-13
強化学習アルゴリズム
攻撃検出
脆弱性分析

EAD: Elastic-Net Attacks to Deep Neural Networks via Adversarial Examples

Authors: Pin-Yu Chen, Yash Sharma, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh | Published: 2017-09-13 | Updated: 2018-02-10
モデルの頑健性保証
対抗的学習
敵対的サンプル

Ensemble Methods as a Defense to Adversarial Perturbations Against Deep Neural Networks

Authors: Thilo Strauss, Markus Hanselmann, Andrej Junginger, Holger Ulmer | Published: 2017-09-11 | Updated: 2018-02-08
モデルの頑健性保証
モデル性能評価
ロバスト性向上

A Neural Network Architecture Combining Gated Recurrent Unit (GRU) and Support Vector Machine (SVM) for Intrusion Detection in Network Traffic Data

Authors: Abien Fred Agarap | Published: 2017-09-10 | Updated: 2019-02-07
モデル性能評価
攻撃検出
機械学習技術

Towards Proving the Adversarial Robustness of Deep Neural Networks

Authors: Guy Katz, Clark Barrett, David L. Dill, Kyle Julian, Mykel J. Kochenderfer | Published: 2017-09-08
モデルの頑健性保証
ロバスト性向上
対抗的学習