Baoyuan Wu

Prototype-supervised Adversarial Network for Targeted Attack of Deep Hashing

2021 · arXiv (Cornell University)

Due to its powerful capability of representation learning and high-efficiency computation, deep hashing has made significant progress in large-scale image retrieval. However, deep hashing networks are vulnerable to adversarial examples, which is a practical secure …

BlackboxBench: A Comprehensive Benchmark of Black-box Adversarial Attacks

2023 · arXiv (Cornell University)

Adversarial examples are well-known tools to evaluate the vulnerability of deep neural networks (DNNs). Although lots of adversarial attack algorithms have been developed, it's still challenging in the practical scenario that the model's parameters and …

BackdoorBench: A Comprehensive Benchmark and Analysis of Backdoor Learning

2024 · arXiv (Cornell University)

As an emerging and vital topic for studying deep neural networks' vulnerability (DNNs), backdoor learning has attracted increasing interest in recent years, and many seminal backdoor attack and defense algorithms are being developed successively or …