Linear and non-linear machine learning attacks on physical unclonable functions
Authors: Michael Lachner | Published: 2023-01-06
ウォーターマーキング
REAP: A Large-Scale Realistic Adversarial Patch Benchmark
Authors: Nabeel Hingun, Chawin Sitawarin, Jerry Li, David Wagner | Published: 2022-12-12 | Updated: 2023-08-18
HashVFL: Defending Against Data Reconstruction Attacks in Vertical Federated Learning
Authors: Pengyu Qiu, Xuhong Zhang, Shouling Ji, Chong Fu, Xing Yang, Ting Wang | Published: 2022-12-01 | Updated: 2024-01-22
Tight Certification of Adversarially Trained Neural Networks via Nonconvex Low-Rank Semidefinite Relaxations
Authors: Hong-Ming Chiu, Richard Y. Zhang | Published: 2022-11-30 | Updated: 2023-06-14
Traditional Classification Neural Networks are Good Generators: They are Competitive with DDPMs and GANs
Authors: Guangrun Wang, Philip H. S. Torr | Published: 2022-11-27 | Updated: 2022-12-08
FedTracker: Furnishing Ownership Verification and Traceability for Federated Learning Model
Authors: Shuo Shao, Wenyuan Yang, Hanlin Gu, Zhan Qin, Lixin Fan, Qiang Yang, Kui Ren | Published: 2022-11-14 | Updated: 2024-03-02
Unlearning Graph Classifiers with Limited Data Resources
Authors: Chao Pan, Eli Chien, Olgica Milenkovic | Published: 2022-11-06 | Updated: 2023-07-01
Unclonability and Quantum Cryptanalysis: From Foundations to Applications
Authors: Mina Doosti | Published: 2022-10-31
Multi-view Representation Learning from Malware to Defend Against Adversarial Variants
Authors: James Lee Hu, Mohammadreza Ebrahimi, Weifeng Li, Xin Li, Hsinchun Chen | Published: 2022-10-25
Towards Adversarial Purification using Denoising AutoEncoders
Authors: Dvij Kalaria, Aritra Hazra, Partha Pratim Chakrabarti | Published: 2022-08-29