Certified Robustness

Amplifying Machine Learning Attacks Through Strategic Compositions

Authors: Yugeng Liu, Zheng Li, Hai Huang, Michael Backes, Yang Zhang | Published: 2025-06-23
Membership Disclosure Risk
Certified Robustness
Adversarial attack

DUMB and DUMBer: Is Adversarial Training Worth It in the Real World?

Authors: Francesco Marchiori, Marco Alecci, Luca Pajola, Mauro Conti | Published: 2025-06-23
Model Architecture
Certified Robustness
Adversarial Attack Analysis

Unsourced Adversarial CAPTCHA: A Bi-Phase Adversarial CAPTCHA Framework

Authors: Xia Du, Xiaoyuan Liu, Jizhe Zhou, Zheng Lin, Chi-man Pun, Zhe Chen, Wei Ni, Jun Luo | Published: 2025-06-12
Certified Robustness
Adversarial Learning
Adversarial Attack Detection

Adversarial Surrogate Risk Bounds for Binary Classification

Authors: Natalie S. Frank | Published: 2025-06-11
Certified Robustness
Convergence Analysis
Function Boundary Pair Formation

Enhancing Adversarial Robustness with Conformal Prediction: A Framework for Guaranteed Model Reliability

Authors: Jie Bao, Chuangyin Dang, Rui Luo, Hanwei Zhang, Zhixin Zhou | Published: 2025-06-09
Certified Robustness
Robust Optimization
Adversarial Attack Methods

LLM Unlearning Should Be Form-Independent

Authors: Xiaotian Ye, Mengqi Zhang, Shu Wu | Published: 2025-06-09
Training Method
Certified Robustness
非意味的リダイレクション

Adversarially Pretrained Transformers may be Universally Robust In-Context Learners

Authors: Soichiro Kumano, Hiroshi Kera, Toshihiko Yamasaki | Published: 2025-05-20
Certified Robustness
Relationship between Robustness and Privacy
Adversarial Learning

Quantum Support Vector Regression for Robust Anomaly Detection

Authors: Kilian Tscharke, Maximilian Wendlinger, Sebastian Issel, Pascal Debus | Published: 2025-05-02 | Updated: 2025-05-13
Certified Robustness
Anomaly Detection Method
Role of Quantum Machine Learning

A Cryptographic Perspective on Mitigation vs. Detection in Machine Learning

Authors: Greg Gluch, Shafi Goldwasser | Published: 2025-04-28 | Updated: 2025-07-10
Certified Robustness
Adversarial attack
Computational Problem

Evaluating the Vulnerability of ML-Based Ethereum Phishing Detectors to Single-Feature Adversarial Perturbations

Authors: Ahod Alghuried, Ali Alkinoon, Abdulaziz Alghamdi, Soohyeon Choi, Manar Mohaisen, David Mohaisen | Published: 2025-04-24
Detection Rate of Phishing Attacks
Certified Robustness
Adversarial Example Detection