62 citations · 85 across the 14 of their papers we have counts for
5 papers · 1 filter
Efficient Trigger Word Insertion
Yueqi Zeng, Ziqiang Li, Pengfei Xia +2
With the boom in the natural language processing (NLP) field these years, backdoor attacks pose immense threats against deep neural network models. However, previous works hardly c…
Explore the Effect of Data Selection on Poison Efficiency in Backdoor Attacks
Ziqiang Li, Pengfei Xia, Hong Sun +3
As the number of parameters in Deep Neural Networks (DNNs) scales, the thirst for training data also increases. To save costs, it has become common for users and enterprises to del…
Efficient Backdoor Attacks for Deep Neural Networks in Real-world Scenarios
Ziqiang Li, Hong Sun, Pengfei Xia +4
Recent deep neural networks (DNNs) have came to rely on vast amounts of training data, providing an opportunity for malicious attackers to exploit and contaminate the data to carry…
A Proxy Attack-Free Strategy for Practically Improving the Poisoning Efficiency in Backdoor Attacks
Ziqiang Li, Hong Sun, Pengfei Xia +6
Poisoning efficiency is crucial in poisoning-based backdoor attacks, as attackers aim to minimize the number of poisoning samples while maximizing attack efficacy. Recent studies h…
Frequency Decomposition to Tap the Potential of Single Domain for Generalization
Qingyue Yang, Hongjing Niu, Pengfei Xia +2
Domain generalization (DG), aiming at models able to work on multiple unseen domains, is a must-have characteristic of general artificial intelligence. DG based on single source do…