ML Security
NDSS 2025 – Probe-Me-Not: Protecting Pre-trained Encoders From Malicious Probing
Session 7D: ML Security Authors, Creators & Presenters: Ruyi Ding (Northeastern University), Tong Zhou (Northeastern University), Lili Su (Northeastern University), Aidong Adam Ding (Northeastern University), Xiaolin Xu (Northeastern University), Yunsi Fei (Northeastern ...
NDSS 2025 – A New PPML Paradigm For Quantized Models
Session 7D: ML Security Authors, Creators & Presenters: Tianpei Lu (The State Key Laboratory of Blockchain and Data Security, Zhejiang University), Bingsheng Zhang (The State Key Laboratory of Blockchain and Data Security, ...
NDSS 2025 – DLBox: New Model Training Framework For Protecting Training Data
Session 7D: ML Security Authors, Creators & Presenters: Jaewon Hur (Seoul National University), Juheon Yi (Nokia Bell Labs, Cambridge, UK), Cheolwoo Myung (Seoul National University), Sangyun Kim (Seoul National University), Youngki Lee ...
NDSS 2025 – Understanding Data Importance In Machine Learning Attacks
Session 7D: ML Security Authors, Creators & Presenters: Rui Wen (CISPA Helmholtz Center for Information Security), Michael Backes (CISPA Helmholtz Center for Information Security), Yang Zhang (CISPA Helmholtz Center for Information Security) ...
NDSS 2025 – AlphaDog: No-Box Camouflage Attacks Via Alpha Channel Oversight
Session 7D: ML Security Authors, Creators & Presenters: Qi Xia (University of Texas at San Antonio), Qian Chen (University of Texas at San Antonio) PAPER AlphaDog: No-Box Camouflage Attacks via Alpha Channel ...
