72 citations · 136 across the 5 of their papers we have counts for
9 papers
Reinforcement Learning-based Black-Box Evasion Attacks to Link Prediction in Dynamic Graphs
Houxiang Fan, Binghui Wang, Pan Zhou +6
Link prediction in dynamic graphs (LPDG) is an important research problem that has diverse applications such as online recommendations, studies on disease contagion, organizational…
LotteryFL: Personalized and Communication-Efficient Federated Learning with Lottery Ticket Hypothesis on Non-IID Datasets
Ang Li, Jingwei Sun, Binghui Wang +4
Federated learning is a popular distributed machine learning paradigm with enhanced privacy. Its primary goal is learning a global model that offers good performance for the partic…
Perturbing Across the Feature Hierarchy to Improve Standard and Strict Blackbox Attack Transferability
Nathan Inkawhich, Kevin J Liang, Binghui Wang +3
We consider the blackbox transfer-based targeted adversarial attack threat model in the realm of deep neural network (DNN) image classifiers. Rather than focusing on crossing decis…
On Certifying Robustness against Backdoor Attacks via Randomized Smoothing
Binghui Wang, Xiaoyu Cao, Jinyuan jia +1
Backdoor attack is a severe security threat to deep neural networks (DNNs). We envision that, like adversarial examples, there will be a cat-and-mouse game for backdoor attacks, i.…
Certified Robustness of Community Detection against Adversarial Structural Perturbation via Randomized Smoothing
Jinyuan Jia, Binghui Wang, Xiaoyu Cao +1
Community detection plays a key role in understanding graph structure. However, several recent studies showed that community detection is vulnerable to adversarial structural pertu…
Certified Robustness for Top-k Predictions against Adversarial Perturbations via Randomized Smoothing
Jinyuan Jia, Xiaoyu Cao, Binghui Wang +1
It is well-known that classifiers are vulnerable to adversarial perturbations. To defend against adversarial perturbations, various certified robustness results have been derived.…