On the Exploitability of Instruction Tuning
Authors: Manli Shu, Jiongxiao Wang, Chen Zhu, Jonas Geiping, Chaowei Xiao, Tom Goldstein | Published: 2023-06-28 | Updated: 2023-10-28
敵対的攻撃検出
Robust Transferable Feature Extractors: Learning to Defend Pre-Trained Networks Against White Box Adversaries
Authors: Alexander Cann, Ian Colbert, Ihab Amer | Published: 2022-09-14
A Tale of HodgeRank and Spectral Method: Target Attack Against Rank Aggregation Is the Fixed Point of Adversarial Game
Authors: Ke Ma, Qianqian Xu, Jinshan Zeng, Guorong Li, Xiaochun Cao, Qingming Huang | Published: 2022-09-13
Defend Data Poisoning Attacks on Voice Authentication
Authors: Ke Li, Cameron Baird, Dan Lin | Published: 2022-09-09 | Updated: 2023-07-07
SAGE: Software-based Attestation for GPU Execution
Authors: Andrei Ivanov, Benjamin Rothenberger, Arnaud Dethise, Marco Canini, Torsten Hoefler, Adrian Perrig | Published: 2022-09-07
RX-ADS: Interpretable Anomaly Detection using Adversarial ML for Electric Vehicle CAN data
Authors: Chathurika S. Wickramasinghe, Daniel L. Marino, Harindra S. Mavikumbure, Victor Cobilean, Timothy D. Pennington, Benny J. Varghese, Craig Rieger, Milos Manic | Published: 2022-09-05
A Deep Learning Approach to Create DNS Amplification Attacks
Authors: Jared Mathews, Prosenjit Chatterjee, Shankar Banik, Cory Nance | Published: 2022-06-29
Adversarial Robustness is at Odds with Lazy Training
Authors: Yunjuan Wang, Enayat Ullah, Poorya Mianjy, Raman Arora | Published: 2022-06-18 | Updated: 2022-10-17
Holistic Adversarial Robustness of Deep Learning Models
Authors: Pin-Yu Chen, Sijia Liu | Published: 2022-02-15 | Updated: 2023-01-05
Pixle: a fast and effective black-box attack based on rearranging pixels
Authors: Jary Pomponi, Simone Scardapane, Aurelio Uncini | Published: 2022-02-04