Work

MAP: Masked Adversarial Perturbation for Boosting Black-Box Attack Transferability

Year: 2025

Type: article

Source: IEEE Transactions on Image Processing

DOI: 10.1109/tip.2025.3586485

Authors: Kaige Li, Maoxian Wan, Qichuan Geng, Weimin Shi, Xiaochun Cao, Zhong Zhou

Institutions: State Key Laboratory of Virtual Reality Technology and Systems, Beihang University, Capital Normal University, Sun Yat-sen University

Language: English

Topic: Adversarial Robustness in Machine Learning

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: closed

Funder: National Natural Science Foundation of China

Awards: G1343645032, G5099911738

OpenAlex ID: W4412403764

FWCI: 1.632

Cites: 58

Cited by: 4

Related to: 10