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# Project Details
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The goal of the course project is to dive more deeply into a particular topic.
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The project can be completed either **individually** or in **groups of two**. A
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good project could potentially lead to a publishable result. This project could
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take different forms:
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The project can be completed in **groups of two or three**. A good project could
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lead to some kind of publication. This project could take different forms:
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- **Conceptual**: Extend a technique or explore a new application.
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- **Experience report**: Experiment with an existing implementation, trying out
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different examples and describing the overall experience. Or make a new
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implementation.
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- **Literature survey**: Select a couple (3-5) of related papers in a recent
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research area. Summarize the significance, then compare and contrast.
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- **Conceptual**: Develop a new technique, extend an existing method, or explore
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a new application
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- **Experience report**: Experiment with an implementation, trying out different
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examples and describing the overall experience. Or implement something new.
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- **Literature survey**: Select a couple (3-5) of closely related papers in a
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recent research area. Summarize the significance, then compare and contrast.
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- **Other**: Feel free to propose other kinds of projects.
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If at any point you have trouble finding a project, run into difficulties, or
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just want some advice, **please come talk to me** and I will try to help you get
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unstuck.
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just don't know what to do, **please come talk to me as soon as possible** and I
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will help you get unstuck.
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## Deliverables
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@ -38,8 +37,7 @@ should be clear what remains to be done.
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Besides the milestones, the main deliverable of the project will be a written
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final report, around **15-20 pages** in length. Reports should be written in a
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research paper style, covering the following broad areas in some reasonable
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order:
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research paper style, covering the following areas in some reasonable order:
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- **Introduce** the problem and the motivation.
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- **Review** background and preliminary material.
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- **Evaluate** the results.
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- **Survey** related work.
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At the end of the course, each group will give a brief project presentation in
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class.
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At the end of the course, each group will give a brief project presentation.
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## Deadlines
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# Welcome to CS 839!
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# Welcome to CS 763!
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This is a graduate-level course covering advanced topics in security and
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privacy. We will focus on four areas at the current research frontier: (1)
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differential privacy, (2) applied cryptography, (3) language-based security, and
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(4) adversarial machine learning. Students will read, present, and discuss
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This is a graduate-level course covering advanced topics in security and privacy
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in data science. We will focus on four areas at the current research frontier:
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(1) differential privacy, (2) applied cryptography, (3) language-based security,
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and (4) adversarial machine learning. Students will read, present, and discuss
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papers from the research literature (i.e., conference and journal papers), and
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complete a final project.
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## Logistics
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- **Course**: CS 839, Fall 2018
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- **Location**: CS 1325
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- **Time**: Mondays and Wednesdays, 4:00-5:15
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- **Course**: CS 763, Fall 2019
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- **Location**: CS 1263
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- **Time**: Monday, Wednesday, Friday, 2:00-3:15
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For the first ten weeks, lectures will be held on Monday, Wednesday, and Friday.
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In the remaining five weeks, you will work on your course projects. Though there
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are no lectures scheduled in this period, I am available to meet as needed.
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## Mailing List
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Please use the mailing list if you want to contact the whole course:
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- [compsci839-1-f18@lists.wisc.edu](compsci839-1-f18@lists.wisc.edu)
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- <mailto:compsci763-1-f19@lists.wisc.edu>
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All registered students should be on this list. If you are not registered but
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would like to follow along, please let me know and I will try to add you.
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would like to follow along, please let me know and I will add you.
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Otherwise, you can contact me directly. To ensure that your email goes to the
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right place, please start the subject with **CS839**.
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right place, please start the subject with **CS763**.
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## Course Staff
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- **Instructor**: [Justin Hsu](https://justinh.su)
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- **Email**: justhsu@cs.wisc.edu
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- **Email**: <mailto:justhsu@cs.wisc.edu>
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- **Location**: CS 6379
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- **Office hours**: By appointment
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Lectures will be loosely organized around four **modules**: differential
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privacy, applied cryptography, language-based security, and adversarial machine
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learning. I will give most of the lectures for the first module (differential
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privacy). For the other modules, I will give an overview lecture surveying the
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topic and background material. Then, each student will lead one lecture,
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presenting a paper and guiding the discussion.
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Lectures will be loosely organized around three core modules: differential
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privacy, adversarial machine learning, and applied cryptography. We will also
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cover two advanced modules: algorithmic fairness, and PL and verification
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techniques.
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This is a graduate seminar, so not all lectures are set in stone and there is
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considerable flexibility in the material. If you are interested in something not
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@ -34,6 +32,12 @@ a few sentences per question. These questions will help you check that you have
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understood the papers---they are not meant to be very difficult or
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time-consuming and they will not be graded in detail.
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## Course Materials
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For differential privacy, we will use the textbook *Algorithmic Foundations of
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Data Privacy* (AFDP) by Cynthia Dwork and Aaron Roth, available
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[here](https://www.cis.upenn.edu/~aaroth/Papers/privacybook.pdf).
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## Course Project
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The other main component is the **course project**. You will work individually
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The first key date is **September 19**. Before this date, you should:
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The first key date is **September 16**. By this date, you should:
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- **Check in** with me briefly.
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- **Sign up** to present a paper.
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you should have an initial direction.
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## Project Deadlines
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- Milestone 1: **October 17**
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- Milestone 2: **November 14**
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- Final writeup and presentation: **December 14**
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- Milestone 1: **October 7**
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- Milestone 2: **November 8**
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- Final writeup and presentation: **December 11** (TBD)
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# Calendar (Tentative)
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# Calendar
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For differential privacy, we will use the textbook *Algorithmic Foundations of
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Data Privacy* (AFDP) by Cynthia Dwork and Aaron Roth, available
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[here](https://www.cis.upenn.edu/~aaroth/Papers/privacybook.pdf).
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Date | Topic | Presenter
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Date | Topic | Notes
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:----:|-------|:---------:
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| <center> <h4> **Differential Privacy** </h4> </center> |
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9/5 | [Course welcome, introducing differential privacy](../resources/slides/lecture-welcome.html) <br> **Paper:** Keshav. [*How to Read a Paper*](https://web.stanford.edu/class/ee384m/Handouts/HowtoReadPaper.pdf). | Justin
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9/10 | Basic private mechanisms <br> **Reading:** AFDP 3.2, 3.3 | Justin
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9/12 | Composition and closure properties <br> **Reading:** AFDP 3.5 | Justin
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9/17 | What does differential privacy actually mean? <br> **Reading:** McSherry. [*Lunchtime for Differential Privacy*](https://github.com/frankmcsherry/blog/blob/master/posts/2016-08-16.md) (see also these [two](https://github.com/frankmcsherry/blog/blob/master/posts/2016-06-14.md) [posts](https://github.com/frankmcsherry/blog/blob/master/posts/2016-08-29.md)) | Justin
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9/19 | Exponential mechanism <br> **Paper:** McSherry and Talwar. [*Mechanism Design via Differential Privacy*](http://kunaltalwar.org/papers/expmech.pdf). <br> <center> <h5> **Due: Project topics and groups** </h5> </center> | Justin
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**9/21 (FRI)** | Identity-Based Encryption from the Diffie-Hellman Assumption <br> <center> **SPECIAL TIME AND PLACE: 4 PM, CS 1240** </center> | Sanjam Garg
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9/24 | Advanced mechanisms <br> Report-noisy-max, Sparse Vector Technique, and Private Multiplicative Weights <br> **Reading:** AFDP 3.3, 3.5, 4.2 | Justin
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9/26 | Privacy for data streams <br> **Paper:** Chan, Shi, and Song. [*Private and Continual Release of Statistics*](https://eprint.iacr.org/2010/076.pdf). | Yinglun
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10/1 | Local differential privacy <br> **Paper:** Erlingsson, Pihur, and Korolova. [*RAPPOR: Randomized Aggregatable Privacy-Preserving Ordinal Response*](https://arxiv.org/pdf/1407.6981.pdf). | Justin
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9/4 | [Course welcome](../resources/slides/lecture-welcome.html) <br> **Paper:** Keshav. [*How to Read a Paper*](https://web.stanford.edu/class/ee384m/Handouts/HowtoReadPaper.pdf). |
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9/6 | |
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9/9 | |
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9/11 | |
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9/13 | |
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| <center> <h4> **Adversarial Machine Learning** </h4> </center> |
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10/3 | [AML: overview and basics](../resources/slides/somesh-aml.pdf) <br> <center> **GUEST LECTURE** </center> | Somesh Jha
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10/8 | History of Adversarial ML <br> **Paper:** Biggio and Roli. [*Wild Patterns: Ten Years After the Rise of Adversarial Machine Learning*](https://arxiv.org/pdf/1712.03141). | Meghana
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10/10 | Adversarial examples <br> **Paper:** Szegedy, Zaremba, Sutskever, et al. [*Intriguing Properties of Neural Networks*](https://arxiv.org/pdf/1312.6199.pdf). | Shimaa
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10/15 | <center> **NO CLASS: INSTRUCTOR AWAY** </center> |
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10/17 | <center> **NO CLASS: INSTRUCTOR AWAY** <br> <center> <h5> **Due: Milestone 1** </h5> </center> |
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10/22 | Adversarial examples <br> **Paper:** Goodfellow, Schlens, and Szegedy. [*Explaining and Harnessing Adversarial Examples*](https://arxiv.org/abs/1412.6572). | Kyrie
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10/24 | Real-world attacks <br> **Paper:** Eykholt, Evtimov, Fernandes, et al. [*Robust Physical-World Attacks on Deep Learning Models*](https://arxiv.org/pdf/1707.08945.pdf). | Hiba
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10/29 | Detection methods <br> **Paper:** Carlini and Wagner. [*Towards Evaluating the Robustness of Neural Networks*](https://arxiv.org/pdf/1608.04644.pdf). | Yiqin
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10/31 | Detection methods <br> **Paper:** Carlini and Wagner. [*Adversarial Examples Are Not Easily Detected: Bypassing Ten Detection Methods*](https://arxiv.org/pdf/1705.07263.pdf). | Junxiong
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11/5 | Defensive measures <br> **Paper:** Steinhardt, Koh, and Liang. [*Certified Defenses for Data Poisoning Attacks*](https://arxiv.org/pdf/1706.03691.pdf). | Yaman
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11/7 | Defensive measures <br> **Paper:** Madry, Makelov, Schmidt, Schmidt, Tsipras, and Valdu. [*Towards Deep Learning Models Resistant to Adversarial Attacks*](https://arxiv.org/pdf/1706.06083.pdf). | Maddie
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| <center> <h4> **Cryptographic Techniques** </h4> </center> |
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11/12 | Applied crypto: overview and basics | Justin
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11/14 | Verifiable differential privacy <br> **Paper:** Narayan, Feldman, Papadimitriou, and Haeberlen. [*Verifiable Differential Privacy*](https://www.cis.upenn.edu/~ahae/papers/verdp-eurosys2015.pdf). <br> <center> <h5> **Due: Milestone 2** </h5> </center> | Fayi
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11/19 | Homomorphic encryption <br> **Paper:** Halevi and Shoup. [*Algorithms in HElib*](https://www.shoup.net/papers/helib.pdf). | Yue
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| <center> <h4> **Language-Based Security** </h4> </center> |
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11/21 | [Language-based security: overview and basics](../resources/slides/lecture-langsec.html) | Justin
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11/26 | Languages for privacy <br> **Paper:** Reed and Pierce. [*Distance Makes the Types Grow Stronger: A Calculus for Differential Privacy*](https://www.cis.upenn.edu/~bcpierce/papers/dp.pdf). | Sam
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11/28 | Cryptε: Crypto-Assisted Differential Privacy <br> <center> **GUEST LECTURE** </center> | Amrita Roy Chowdhury
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12/3 | Languages for authenticated datastructures <br> **Paper:** Miller, Hicks, Katz, and Shi. [*Authenticated Data Structures, Generically*](https://www.cs.umd.edu/~mwh/papers/gpads.pdf). | Zichuan
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12/5 | Languages for oblivous computing <br> **Paper:** Zahur and Evans. [*Obliv-C: A Language for Extensible Data-Oblivious Computation*](https://eprint.iacr.org/2015/1153.pdf). | Zhiyi
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12/10 | Languages for information flow <br> **Paper:** Griffin, Levy, Stefan, et al. [*Hails: Protecting Data Privacy in Untrusted Web Applications*](https://www.usenix.org/system/files/conference/osdi12/osdi12-final-35.pdf). | Arjun
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12/12 | Timing channels <br> **Paper:** Wang, Ferraiuolo, Zhang, Myers, and Suh. [*SecDCP: Secure Dynamic Cache Partitioning for Efficient Timing Channel Protection*](http://www.csl.cornell.edu/~yao/docs/DAC2016.pdf). | Yan
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**12/14 (FRI)** | Project presentations <br> <center> **SPECIAL TIME AND PLACE: 10 AM, CS 2310** </center> <center> <h5> **Due: Final project reports** </h5> </center> |
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9/16 | |
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9/18 | |
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9/20 | |
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9/23 | |
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9/25 | |
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9/27 | |
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| <center> <h4> **Applied Cryptography** </h4> </center> |
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9/30 | |
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10/2 | |
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10/4 | |
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10/7 | |
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10/9 | |
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10/11 | |
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| <center> <h4> **Advanced Topic: Algorithmic Fairness** </h4> </center> |
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10/14 | |
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10/16 | |
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10/18 | |
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10/21 | |
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10/23 | |
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10/25 | |
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| <center> <h4> **Advanced Topic: PL and Verification** </h4> </center> |
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10/28 | |
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10/30 | |
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11/1 | |
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11/4 | |
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11/6 | |
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11/8 | |
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| <center> <h4> **No Lectures: Work on Projects** </h4> </center> |
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12/11 (TBD) | Project Presentations |
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site_name: 'CS 839: Topics in Security and Privacy Technologies (Fall 2018)'
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site_name: 'CS 763: Security and Privacy in Data Science (Fall 2019)'
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site_url: ''
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repo_url: 'https://git.justinh.su/justhsu/cs839'
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site_description: 'Course webpage for CS 839: Topics in Security and Privacy Technologies (Fall 2018)'
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repo_url: 'https://git.justinh.su/justhsu/cs763'
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site_description: 'Course webpage for CS 763: Security and Privacy in Data Science (Fall 2019)'
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site_author: 'Justin Hsu'
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theme:
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logo: 'assets/images/favicon.ico'
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favicon: 'assets/images/favicon.ico'
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palette:
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primary: blue grey
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accent: blue grey
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primary: red
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accent: red
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nav:
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- Home:
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