Privacy Enhancing Technologies Yang Zhang, Lucjan Hanzlik, Robert K√ľnnemann

Registration for this course is open until Monday, 23.04.2018 00:00.

News

16.04.2018

about slides

Hi,

The lecture slides are in "Information-> Materials" in the CMS system.

Cheers,

Yang

11.04.2018

Programming environment setup

Hi all,

the first lecture (next Monday) will have a small practice session. 

Please install Anaconda:

https://www.anaconda.com/download/

and gensim:

https://radimrehurek.com/gensim/install.html

before the lecture starts.

We will use python's... Read more

Hi all,

the first lecture (next Monday) will have a small practice session. 

Please install Anaconda:

https://www.anaconda.com/download/

and gensim:

https://radimrehurek.com/gensim/install.html

before the lecture starts.

We will use python's data science packages (pandas, numpy, and scipy) for the data privacy part of the lecture, it is recommended to get familiar with these packages. 

09.04.2018

No lecture on April 23rd

The lecture on April 23rd is canceled due to conference travel.

 

Privacy Enhancing Technologies

Overview


This course will cover the topic of privacy from three aspects.

  • Data privacy
  • Cryptographic techniques
  • Formal methods

More information on the lecture will become available later on.

 

Logistics


Location: E9 1, Lecture hall

Lecturers: Yang Zhang, Lucjan Hanzlik, and Robert Künnemann

Time: Monday, 12:15-14:00 (Starting from April 16th) 

Contact: Yang Zhang (yang.zhang@cispa.saarland)

Office hour for data privacy: Tuesday, 13:30-16:30; Friday, 13:30-16:30, 3.19, E9.1 (Please send email for an appointment beforehand!)

 

Schedule


 

2018.04.16 Social Network Privacy: Personal attribute inference and graph de-anonymization (Yang Zhang)
2018.04.30 Location Privacy: Location Prediction and Link Prediction (Yang Zhang)
2018.05.07 Genomic Privacy (Yang Zhang)
2018.05.14 Privacy in Machine Learning: Membership Inference and Model Extraction (Yang Zhang)
2018.05.21 Differential Privacy (guest lecture)
2018.05.28 Introduction to Zero-Knowledge Proofs (Lucjan Hanzlik)
2018.06.04 Privacy Preserving Signature Schemes (Lucjan Hanzlik)
2018.06.11 ePassport and its Cryptographic Algorithms (Lucjan Hanzlik)
2018.06.18 Case Study: German eID (Lucjan Hanzlik)
2018.06.25 Privacy in Protocols: the static case (Robert Künnemann)
2018.07.02 Privacy in Protocols: the active case (Robert Künnemann)
2018.07.09 Privacy and other equivalence notions (Robert Künnemann)
2018.07.16 Course Summary

 

Grading


 

The data privacy part of this lecture will be graded based on a semester-long project.

The cryptography and formal method parts will have a final written exam.

The project will constitute 50% of the final grade and the exam will constitute the other 50%. Exercises are not considered for the graded, but for exam admission.

To be able to enter the final exam, a student needs to have:

  • to pass (50%) the project
  • at least 50% of the maximal exercise score for the sum of both exercise sheet (one for cryptography, one for formal methods).

 

 

 

 




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