56 citations · 134 across the 6 of their papers we have counts for
7 papers
Progressive-Scale Boundary Blackbox Attack via Projective Gradient Estimation
Jiawei Zhang, Linyi Li, Huichen Li +3
Boundary based blackbox attack has been recognized as practical and effective, given that an attacker only needs to access the final model prediction. However, the query efficiency…
Nonlinear Projection Based Gradient Estimation for Query Efficient Blackbox Attacks
Huichen Li, Linyi Li, Xiaojun Xu +3
Gradient estimation and vector space projection have been studied as two distinct topics. We aim to bridge the gap between the two by investigating how to efficiently estimate grad…
Exploring Adversarial Robustness of Multi-Sensor Perception Systems in Self Driving
James Tu, Huichen Li, Xinchen Yan +6
Modern self-driving perception systems have been shown to improve upon processing complementary inputs such as LiDAR with images. In isolation, 2D images have been found to be extr…
QEBA: Query-Efficient Boundary-Based Blackbox Attack
Huichen Li, Xiaojun Xu, Xiaolu Zhang +2
Machine learning (ML), especially deep neural networks (DNNs) have been widely used in various applications, including several safety-critical ones (e.g. autonomous driving). As a…
Detecting AI Trojans Using Meta Neural Analysis
Xiaojun Xu, Qi Wang, Huichen Li +3
In machine learning Trojan attacks, an adversary trains a corrupted model that obtains good performance on normal data but behaves maliciously on data samples with certain trigger…
Data Poisoning Attack against Unsupervised Node Embedding Methods
Mingjie Sun, Jian Tang, Huichen Li +4
Unsupervised node embedding methods (e.g., DeepWalk, LINE, and node2vec) have attracted growing interests given their simplicity and effectiveness. However, although these methods…
A Machine Learning Approach To Prevent Malicious Calls Over Telephony Networks
Huichen Li, Xiaojun Xu, Chang Liu +6
Malicious calls, i.e., telephony spams and scams, have been a long-standing challenging issue that causes billions of dollars of annual financial loss worldwide. This work presents…