DeepCleanse: A Black-box Input SanitizationFramework Against Backdoor Attacks on DeepNeural Networks
By Bao Gia Doan, Ehsan Abbasnejad, Damith Chinthana Ranasinghe. 2019
7 citations recorded by the source corpus.
Subfields: Safety, Robustness & Interpretability
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Safety, Robustness & Interpretability
- Congzheng Song
- Vitaly Shmatikov
- Eugene Bagdasarian
- Roei Schuster
- Eran Tromer
- Reza Shokri
- Prateek Mittal
- Vitaly Feldman
Citations in the corpus
- You Autocomplete Me: Poisoning Vulnerabilities in Neural Code Completion (2020, background): “Many defenses have been proposed in the literature [12, 15, 18, 22, 27, 29, 35, 36, 46, 58, 59, 62, 65, 66].”
- Blind Backdoors in Deep Learning Models (2020, methodology): “Model anomalies SentiNet [12], Spectral signatures [82, 91], Fine-pruning [50], NeuronInspect [34], Activation clustering [9], SCAn [85], DeepCleanse [17], NNoculation [94], MNTD [97]”