UWisconsin CS 763: Security and Privacy in Data Science (Previously CS 839: Topics in Security and Privacy)
You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
 
 
 
 

2.3 KiB

Calendar (Tentative)

Date Topic Presenter
9/5 Course welcome JH
Differential Privacy
9/10 Definition and Basic Mechanisms JH
9/12 What does Differential Privacy mean? JH
9/17 Composition and closure properties JH
9/19 Exponential mechanism
Paper: McSherry and Talwar. Mechanism Design via Differential Privacy.
JH
9/24 Streaming privacy: counters
Paper: Chan, Shi, and Song. Private and Continual Release of Statistics.
9/26 Advanced mechanisms: Report-noisy-max JH
10/1 Advanced mechanisms: Sparse Vector JH
10/3 Advanced mechanisms: Private multiplicative weights
Paper: Hardt, Ligett, and McSherry. A Simple and Practical Algorithm for Differentially Private Data Release.
10/8 Local differential privacy (theory) JH
10/10 Local differential privacy (practice)
Paper: Erlingsson, Pihur, and Korolova. RAPPOR: Randomized Aggregatable Privacy-Preserving Ordinal Response.
Cryptographic Techniques
10/15 Crypto: overview and basics JH
10/17 Zero-knowledge proofs
Paper:
10/22 Oblivious transfer and SMC
Paper:
10/24 Oblivious transfer and SMC
Paper:
10/29 Fully homomorphic encryption and verifiable computing
Paper:
10/31 Fully homomorphic encryption and verifiable computing
Paper:
Language-Based Security
11/5 LangSec: overview and basics JH
11/7 Secure Information Flow
Paper:
11/12 Secure Information Flow
Paper:
11/14 Languages for privacy
Paper:
11/19 Languages for privacy
Paper:
11/21 Symbolic cryptography
Paper:
Adversarial Machine Learning
11/26 AML: overview and basics JH
11/28 Adversarial examples
Paper:
12/3 Adversarial examples
Paper:
12/5 Training-time attacks
Paper:
12/10 Training-time attacks
Paper:
12/12 Model-theft attacks
Paper: