AIセキュリティポータルbot

Reliable Federated Learning for Mobile Networks

Authors: Jiawen Kang, Zehui Xiong, Dusit Niyato, Yuze Zou, Yang Zhang, Mohsen Guizani | Published: 2019-10-14
クライアント貢献評価
ブロックチェーン統合
信頼評価

Policy Poisoning in Batch Reinforcement Learning and Control

Authors: Yuzhe Ma, Xuezhou Zhang, Wen Sun, Xiaojin Zhu | Published: 2019-10-13 | Updated: 2019-10-31
強化学習環境
攻撃の評価
攻撃者や悪意のあるデバイス

On Robustness of Neural Ordinary Differential Equations

Authors: Hanshu Yan, Jiawei Du, Vincent Y. F. Tan, Jiashi Feng | Published: 2019-10-12 | Updated: 2022-03-03
モデルの設計や精度
攻撃の評価
防御手法の効果分析

Extraction of Complex DNN Models: Real Threat or Boogeyman?

Authors: Buse Gul Atli, Sebastian Szyller, Mika Juuti, Samuel Marchal, N. Asokan | Published: 2019-10-11 | Updated: 2020-05-27
Out-of-Distribution検出
モデルの設計や精度
攻撃の評価

Hear “No Evil”, See “Kenansville”: Efficient and Transferable Black-Box Attacks on Speech Recognition and Voice Identification Systems

Authors: Hadi Abdullah, Muhammad Sajidur Rahman, Washington Garcia, Logan Blue, Kevin Warren, Anurag Swarnim Yadav, Tom Shrimpton, Patrick Traynor | Published: 2019-10-11
攻撃の評価
敵対的攻撃手法
音声認識技術

Defending Neural Backdoors via Generative Distribution Modeling

Authors: Ximing Qiao, Yukun Yang, Hai Li | Published: 2019-10-10 | Updated: 2019-11-06
バックドア攻撃
攻撃の評価
生成的敵対ネットワーク

Adversarial Training: embedding adversarial perturbations into the parameter space of a neural network to build a robust system

Authors: Shixian Wen, Laurent Itti | Published: 2019-10-09
敵対的サンプル
敵対的攻撃手法
適応型敵対的訓練

Membership Model Inversion Attacks for Deep Networks

Authors: Samyadeep Basu, Rauf Izmailov, Chris Mesterharm | Published: 2019-10-09
攻撃の評価
攻撃者や悪意のあるデバイス
生成的敵対ネットワーク

Defensive Escort Teams via Multi-Agent Deep Reinforcement Learning

Authors: Arpit Garg, Yazied A. Hasan, Adam Yañez, Lydia Tapia | Published: 2019-10-09
リスク評価
実験的検証
強化学習環境

Deep Latent Defence

Authors: Giulio Zizzo, Chris Hankin, Sergio Maffeis, Kevin Jones | Published: 2019-10-09 | Updated: 2020-09-27
敵対的サンプル
敵対的攻撃手法
適応型敵対的訓練