Guarding Machine Learning Hardware Against Physical Side-Channel Attacks
Authors: Anuj Dubey, Rosario Cammarota, Vikram Suresh, Aydin Aysu | Published: 2021-09-01
EG-Booster: Explanation-Guided Booster of ML Evasion Attacks
Authors: Abderrahmen Amich, Birhanu Eshete | Published: 2021-08-31 | Updated: 2021-09-02
Private Multi-Task Learning: Formulation and Applications to Federated Learning
Authors: Shengyuan Hu, Zhiwei Steven Wu, Virginia Smith | Published: 2021-08-30 | Updated: 2023-10-17
Student Surpasses Teacher: Imitation Attack for Black-Box NLP APIs
Authors: Qiongkai Xu, Xuanli He, Lingjuan Lyu, Lizhen Qu, Gholamreza Haffari | Published: 2021-08-29 | Updated: 2022-09-04
Machine Unlearning of Features and Labels
Authors: Alexander Warnecke, Lukas Pirch, Christian Wressnegger, Konrad Rieck | Published: 2021-08-26 | Updated: 2023-08-07
Mitigating Statistical Bias within Differentially Private Synthetic Data
Authors: Sahra Ghalebikesabi, Harrison Wilde, Jack Jewson, Arnaud Doucet, Sebastian Vollmer, Chris Holmes | Published: 2021-08-24 | Updated: 2022-05-19
Semantic-Preserving Adversarial Text Attacks
Authors: Xinghao Yang, Weifeng Liu, James Bailey, Dacheng Tao, Wei Liu | Published: 2021-08-23 | Updated: 2023-03-03
“Adversarial Examples” for Proof-of-Learning
Authors: Rui Zhang, Jian Liu, Yuan Ding, Zhibo Wu, Qingbiao Wang, Kui Ren | Published: 2021-08-21 | Updated: 2022-04-05
OACAL: Finding Module-consistent Specifications to Secure Systems from Weakened User Obligations
Authors: Pengcheng Jiang, Kenji Tei | Published: 2021-08-16 | Updated: 2021-11-02
Privacy-Preserving Machine Learning: Methods, Challenges and Directions
Authors: Runhua Xu, Nathalie Baracaldo, James Joshi | Published: 2021-08-10 | Updated: 2021-09-22