Privacy Enhancing Technologies Yang Zhang

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03.06.2020

Guides on Attacks Implementation

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Dear all,

 

As we mentioned in the seminar, you need to implement three attacks during the seminar, which are Membership Inference Attack, Model Inversion Attack, and Model Stealing Attack(a.k.a Model Extraction Attack).

 

In the... Read more

Dear all,

 

As we mentioned in the seminar, you need to implement three attacks during the seminar, which are Membership Inference Attack, Model Inversion Attack, and Model Stealing Attack(a.k.a Model Extraction Attack).

 

In the first phase, to simplify your tasks and quickly build background knowledge, we have some guides as follows:

  1. You should use a simple convolutional neural network as the basic model for all the three attacks, please refer to the PyTorch tutorial https://pytorch.org/tutorials/beginner/blitz/cifar10_tutorial.html.
  2. We mainly focus on image data and we suggest using the following three datasets: CIFAR10, MNIST, and Fashion-MNIST. You could load the dataset with the python torchvision package, refer to https://pytorch.org/docs/stable/torchvision/datasets.html.
  3. As to the membership inference attack, you only need to implement the "attack one" in the paper titled "ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models".
  4. As to the model inversion attack, you only need to implement the basic model inversion attack in Algorithm 1, refer to the paper titled "Model Inversion Attacks that Exploit Confidence Information and Basic Countermeasures".
  5. We will give more information about implementing the model stealing attack next week. You could refer to the paper titled "Stealing Machine Learning Models via Prediction APIs" for some detail in advance.

 

Besides, here is the group information we received so far. I hope no one is missed. :)

1

Julian Augustin,

Mahmoud Fawzi,

Omar Mansour,

Gayathri Vijayan

2

Yu De Lin,

Vikram Vashisth,

David Ahmed,

Mejbah Uddin Shameem,

3

Dominik Sautter

Zubayr Khalid

Maximilian Zöllner

Jan Cloos

4

Dominik Kempter, 

Muhammad Hassan Rashid, 

Leonard Zitzmann,

Barno Kaharova,

5

Rui Wen,

Yugeng Liu,

Yongqing Wang,

Julian Jacques Maurer
6

Benjamin Hollinger

Hasan Md Tusfiqur Alam

Filip Josheski

Rayhanul Islam Rumel

7

Tajbeed Ahmed Chowdhury

Mohammed Raihan Hussain

Thomas Boisvert-Bilodeau

Niraj Premji Sorathiya

 

Best,

Min

27.05.2020

slides for chapter 4 are up

Hi All,

Slides for Chapter 4 are up. Please find it here https://cms.cispa.saarland/pets2020/materials/

 

Thanks,

Ahmed

20.05.2020

Team Building Deadline

Dear all,

 

Today is the deadline for team building. For now, we got 5 teams, the members are as follows.

1

Julian Augustin,

Mahmoud Fawzi,

Omar Mansour,

Gayathri Vijayan

2

Yu De Lin,

... Read more

Dear all,

 

Today is the deadline for team building. For now, we got 5 teams, the members are as follows.

1

Julian Augustin,

Mahmoud Fawzi,

Omar Mansour,

Gayathri Vijayan

2

Yu De Lin,

Vikram Vashisth,

David Ahmed,

Mejbah Uddin Shameem,

3

Dominik Sautter

Zubayr Khalid

Maximilian Zöllner

Jan Cloos

4

Dominik Kempter, 

Muhammad Hassan Rashid, 

Leonard Zitzmann,

Barno Kaharova,

5

Rui Wen,

Yugeng Liu,

Yongqing Wang,

 

If you are not here, please make sure to send your team information to us by the end of today. :)

 

Best,

Min

13.05.2020

slides for chapter 2 are up

please find it here https://cms.cispa.saarland/pets2020/materials/

07.05.2020

Team building forum on google group

Hi, all

I have created a google group for you to build up your team. You may find it by this link, https://groups.google.com/forum/#!managemembers/pets2020.

I have changed some settings, so you could see it without logging in. You need to apply for being a... Read more

Hi, all

I have created a google group for you to build up your team. You may find it by this link, https://groups.google.com/forum/#!managemembers/pets2020.

I have changed some settings, so you could see it without logging in. You need to apply for being a member to see the forum posts, you could log in with any e-mail you could.

If you have any questions, don't hesitate to contact us. 

 

Best,

Min

 
 
 
 
06.05.2020

slides for kick-off and chapter 1 are up

you can find them here

https://cms.cispa.saarland/pets2020/materials/

Cheers,

Yang

30.04.2020

kickoff

Dear all,

the kickoff of our seminar will happen on May 6th, 2020, 12:30-14:00.

Please join via zoom via the following invitation.

Cheers,

Yang

Yang Zhang is inviting you to a scheduled Zoom meeting.

Topic: PETS
Time: This is a recurring meeting... Read more

Dear all,

the kickoff of our seminar will happen on May 6th, 2020, 12:30-14:00.

Please join via zoom via the following invitation.

Cheers,

Yang

Yang Zhang is inviting you to a scheduled Zoom meeting.

Topic: PETS
Time: This is a recurring meeting Meet anytime

Join Zoom Meeting
https://zoom.us/j/93276565793?pwd=UEJWdHdQUWJqUHMvL0VMVWR2MWUzUT09

Meeting ID: 932 7656 5793
Password: 042605
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Show all
 

Privacy Enhancing Technologies

 

Overview


This course will cover the topic of data privacy from four aspects.

  • Social network privacy
  • Location privacy
  • Machine learning privacy
  • Biomedical privacy

 

Prerequisites


  • Basic knowledge of machine learning and data mining
  • Python
  • Security background is not needed

 

Logistics


Location: Online via Zoom

Lecturers: Yang Zhang

Assistants: Min Chen (min.chen@cispa.saarland), Xinlei He (xinlei.he@cispa.saarland), Ahmed Salem (ahmed.salem@cispa.saarland), Yang Zou (yang.zou@cispa.saarland)

Time: Wednesday 12:30 - 14:00

Contact: Min Chen (min.chen@cispa.saarland)

Office hour: Tuesday, 13:30-16:30; Friday, 13:30-16:30, 3.19 (Please send email for an appointment beforehand!)

 

Schedule


2020.05.06 Social Network Privacy: Attributes Inference
2020.05.13 Social Network Privacy: Graph De-anonymization and New Communication Means
2020.05.20 PyTorch Q&A (Ahmed Salem and Allen He)
2020.05.27 Machine Learning Privacy: Membership Inference (Ahmed Salem)
2020.06.03 Machine Learning Privacy: Machine Learning Privacy: Dataset Reconstruction
2020.06.10 Machine Learning Privacy: Model Stealing
2020.06.17 Machine Learning Privacy: Property Inference and Backdoor
2020.06.24 Location Privacy: Unicity, Attribute Inference, and Location Inference
2020.07.01 Differential Privacy 1 (Zhikun Zhang)
2020.07.08 Differential Privacy 2 (Zhikun Zhang)
2020.07.15 Q&A

Grading


The course will be graded by 50% oral exam and 50% semester project.

 

Exam

 



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