Privacy of Machine Learning

Dear all,

The evaluation for the seminar started.

Please use the link below.

https://qualis.uni-saarland.de/eva/?l=1854&p=61k08y

Please do so before February 10th, after that, we can put your scores in LSF.

I'm sorry for the delay but I only got the evaluation link today from Qualis-team.

Again, I wish everyone good luck for the exams.

Best,

Yang

Dear all,

After receiving your responses, we have arranged a schedule for you to give the presentations (see it at the end of this message).
Every Monday from 2 pm to 4 pm, we will have two presenters introduce their preferred papers.

See you next week. :)

Best,
Xinyue

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14.11:
1. Sai Pravallika Tummala, Stealing Machine Learning Models via Prediction APIs
2. Yukun Jiang, Overlearning Reveals Sensitive Attributes

21.11:
3. Shantanu Kumar Rahut, You are who you know and how you behave: Attribute inference attacks via users' social friends and behaviors
4. Janifa Jahan Hossain, Deep Learning with Differential Privacy

28.11:
5. Angelin Mary Jose, Auditing Data Provenance in Text-Generation Models
6. Sarah Breckner, Extracting Training Data from Large Language Models

05.12:
7. Lotfy Abdel Khaliq, Membership Leakage in Label-Only Exposures
8. Tulika Nayak, ML-Doctor: Holistic Risk Assessment of Inference Attacks Against Machine Learning Models

12.12:
9. Aatir Imran, Stealing Hyperparameters in Machine Learning
10. Pranav Subhash Shetty, Stealing Links from Graph Neural Networks