About the Sample Algorithm introduced on purchase dataset

[KaimingZhu]

Hi, Dr. Song. I am now working on the privacy of federated learning, and I have read the article Membership Inference Attacks Against Machine Learning Models . It is very kind of you for sharing the source code.

But I have found my recurrence of attack on purchase dataset don't work well. Could you share the detail of sample algorithm of the simplified purchase dataset? I have found that each commodity are represented as dept, category, company, brand . And I am doubting in these following question :

• If this code is for the attack on purchase dataset?
• The primary key represent a certain commodity is composed by four parts . Do you remember which commodity feature you have used to represent the simplified primary key of each commodity ?
• I have found that you used 600 feature from the commodity list. Can I understand like that : After random sampling on the purchase dataset, we randomly choose 600 columns of the matrix represent which commodity the user has bought. After that, we begin our k-means clustering algorithm, give each input a label?

Thank you for all your assistance.

[csong27]

Please refer to https://github.com/privacytrustlab/ml_privacy_meter for the dataset we used in the paper

[KaimingZhu]

Please refer to https://github.com/privacytrustlab/ml_privacy_meter for the dataset we used in the paper

Thanks a lot :)