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Powerful adversarial attack methods are vital for understanding how to construct robust deep neural networks (DNNs) and thoroughly testing defense techniques. In this project, we propose a black-box adversarial attack algorithm that can defeat both vanilla DNNs and those generated by various defense techniques developed recently. Instead of searching for an “optimal” adversarial example for a benign input to a targeted DNN, our algorithm finds a probability density distribution over a small region centered around the input, such that a sample drawn from this distribution is likely an adversarial example, without the need of accessing the DNN’s internal layers or weights. Our approach is universal as it can successfully attack different neural networks by a single algorithm. It is also strong; according to the testing against 2 vanilla DNNs and 13 defended ones, it outperforms state-of-the-art black-box or white-box attack methods for most test cases. Additionally, our results reveal that adversarial training remains one of the best defense techniques, and the adversarial examples are not as transferable across defended DNNs as them across vanilla DNNs. 

Arylation of carbonyls, one of the most common approaches toward alcohols, has received tremendous attention, as alcohols are important feedstocks and building blocks in organic synthesis. Despite great progress, there is still a great gap to develop an ideal arylation method featuring mild conditions, good functional group tolerance, and readily available starting materials. We now show that electrochemical arylation can fill the gap. By taking advantage of synthetic electrochemistry, commercially available aldehydes (ketones) and benzylic alcohols can be readily arylated to provide a general and scalable access to structurally diverse alcohols (97 examples, >10 gram‐scale). More importantly, convergent paired electrolysis, the ideal but challenging electrochemical technology, was employed to transform low‐value alcohols into more useful alcohols. Detailed mechanism study suggests that two plausible pathways are involved in the redox neutral α‐arylation of benzylic alcohols.

 

Arylation of carbonyls, one of the most common approaches toward alcohols, has received tremendous attention, as alcohols are important feedstocks and building blocks in organic synthesis. Despite great progress, there is still a great gap to develop an ideal arylation method featuring mild conditions, good functional group tolerance, and readily available starting materials. We now show that electrochemical arylation can fill the gap. By taking advantage of synthetic electrochemistry, commercially available aldehydes (ketones) and benzylic alcohols can be readily arylated to provide a general and scalable access to structurally diverse alcohols (97 examples, >10 gram‐scale). More importantly, convergent paired electrolysis, the ideal but challenging electrochemical technology, was employed to transform low‐value alcohols into more useful alcohols. Detailed mechanism study suggests that two plausible pathways are involved in the redox neutral α‐arylation of benzylic alcohols.