文献データベース

IDSGAN: Generative Adversarial Networks for Attack Generation against Intrusion Detection

Authors: Zilong Lin, Yong Shi, Zhi Xue | Published: 2018-09-06 | Updated: 2022-05-08
モデルDoS
性能評価
敵対的学習

Adversarial Reprogramming of Text Classification Neural Networks

Authors: Paarth Neekhara, Shehzeen Hussain, Shlomo Dubnov, Farinaz Koushanfar | Published: 2018-09-06 | Updated: 2019-08-15
タスク適応手法
モデルの頑健性保証
敵対的移転性

Bridging machine learning and cryptography in defence against adversarial attacks

Authors: Olga Taran, Shideh Rezaeifar, Slava Voloshynovskiy | Published: 2018-09-05
モデルの頑健性保証
モデル抽出攻撃の検知
ロバスト性分析

Adversarial Attacks on Node Embeddings via Graph Poisoning

Authors: Aleksandar Bojchevski, Stephan Günnemann | Published: 2018-09-04 | Updated: 2019-05-27
ポイズニング
モデルの頑健性保証
ロバスト性分析

HASP: A High-Performance Adaptive Mobile Security Enhancement Against Malicious Speech Recognition

Authors: Zirui Xu, Fuxun Yu, Chenchen Liu, Xiang Chen | Published: 2018-09-04
ロバスト性向上手法
性能評価
敵対的サンプルの検知

IoTDots: A Digital Forensics Framework for Smart Environments

Authors: Leonardo Babun, Amit Kumar Sikder, Abbas Acar, A. Selcuk Uluagac | Published: 2018-09-03
FR検出メカニズム
IoTセキュリティ
犯罪行為検出

Have You Stolen My Model? Evasion Attacks Against Deep Neural Network Watermarking Techniques

Authors: Dorjan Hitaj, Luigi V. Mancini | Published: 2018-09-03
バックドア攻撃
モデル抽出攻撃の検知
透明性と検証

Adversarial Attack Type I: Cheat Classifiers by Significant Changes

Authors: Sanli Tang, Xiaolin Huang, Mingjian Chen, Chengjin Sun, Jie Yang | Published: 2018-09-03 | Updated: 2019-07-22
トリガーの検知
ロバスト性分析
敵対的移転性

Machine Learning Methods for Network Intrusion Detection

Authors: Mouhammad Alkasassbeh, Mohammad Almseidin | Published: 2018-09-01
データセット評価
性能評価
特徴エンジニアリング

MULDEF: Multi-model-based Defense Against Adversarial Examples for Neural Networks

Authors: Siwakorn Srisakaokul, Yuhao Zhang, Zexuan Zhong, Wei Yang, Tao Xie, Bo Li | Published: 2018-08-31 | Updated: 2019-07-27
モデルアンサンブル
敵対的サンプルの検知
敵対的学習