148 citations · 363 across the 28 of their papers we have counts for
5 papers · 1 filter
On Provable Backdoor Defense in Collaborative Learning
Ximing Qiao, Yuhua Bai, Siping Hu +3
As collaborative learning allows joint training of a model using multiple sources of data, the security problem has been a central concern. Malicious users can upload poisoned data…
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…
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…
Towards Efficient and Secure Delivery of Data for Deep Learning with Privacy-Preserving
Juncheng Shen, Juzheng Liu, Yiran Chen +1
Privacy recently emerges as a severe concern in deep learning, that is, sensitive data must be prohibited from being shared with the third party during deep neural network developm…
Generative Poisoning Attack Method Against Neural Networks
Chaofei Yang, Qing Wu, Hai Li +1
Poisoning attack is identified as a severe security threat to machine learning algorithms. In many applications, for example, deep neural network (DNN) models collect public data a…