# Calendar (Tentative)
Date | Topic | Presenter
:----:|-------|:---------:
| **Differential Privacy**
|
9/5 | Course welcome, introducing differential privacy
**Paper:** Keshav. [*How to Read a Paper*](https://web.stanford.edu/class/ee384m/Handouts/HowtoReadPaper.pdf). | JH
9/10 | Basic private mechanisms | JH
9/12 | What does differential privacy mean? | JH
9/17 | Composition and closure properties
**Due: Project topics and groups**
| JH
9/19 | Exponential mechanism
**Paper:** McSherry and Talwar. [*Mechanism Design via Differential Privacy*](http://kunaltalwar.org/papers/expmech.pdf). | JH
9/24 | Privacy for data streams
**Paper:** Chan, Shi, and Song. [*Private and Continual Release of Statistics*](https://eprint.iacr.org/2010/076.pdf). |
9/26 | Report-noisy-max and the Sparse Vector Technique | JH
10/1 | Answering lots of queries: Private multiplicative weights
**Paper:** Hardt, Ligett, and McSherry. [*A Simple and Practical Algorithm for Differentially Private Data Release*](https://papers.nips.cc/paper/4548-a-simple-and-practical-algorithm-for-differentially-private-data-release.pdf). |
10/3 | Local differential privacy (theory) | JH
10/8 | Local differential privacy (practice)
**Paper:** Erlingsson, Pihur, and Korolova. [*RAPPOR: Randomized Aggregatable Privacy-Preserving Ordinal Response*](https://arxiv.org/pdf/1407.6981.pdf). |
10/10 | More differential privacy
**Paper:** |
10/15 | **NO CLASS: INSTRUCTOR AWAY**
**Due: Milestone 1**
|
| **Cryptographic Techniques**
|
10/17 | Crypto: overview and basics | JH
10/22 | Zero-knowledge proofs and oblivious transfer
**Paper:** |
10/24 | Secure multiparty computation
**Paper:** |
10/29 | Homomorphic encryption
**Paper:** |
10/31 | 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:**
**Due: Milestone 2**
|
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:** |