diff --git a/website/docs/resources/slides/images/aml.jpg b/website/docs/resources/slides/images/aml.jpg new file mode 100644 index 0000000..9f73a98 Binary files /dev/null and b/website/docs/resources/slides/images/aml.jpg differ diff --git a/website/docs/resources/slides/images/crypto-ml.png b/website/docs/resources/slides/images/crypto-ml.png new file mode 100644 index 0000000..864da7c Binary files /dev/null and b/website/docs/resources/slides/images/crypto-ml.png differ diff --git a/website/docs/resources/slides/images/fairness.png b/website/docs/resources/slides/images/fairness.png new file mode 100644 index 0000000..b40027b Binary files /dev/null and b/website/docs/resources/slides/images/fairness.png differ diff --git a/website/docs/resources/slides/images/pl-verif.png b/website/docs/resources/slides/images/pl-verif.png new file mode 100644 index 0000000..71b768c Binary files /dev/null and b/website/docs/resources/slides/images/pl-verif.png differ diff --git a/website/docs/resources/slides/images/privacy.png b/website/docs/resources/slides/images/privacy.png new file mode 100644 index 0000000..ccceaaf Binary files /dev/null and b/website/docs/resources/slides/images/privacy.png differ diff --git a/website/docs/resources/slides/images/there-will-be-math.png b/website/docs/resources/slides/images/there-will-be-math.png new file mode 100644 index 0000000..2ac98f5 Binary files /dev/null and b/website/docs/resources/slides/images/there-will-be-math.png differ diff --git a/website/docs/resources/slides/lecture-welcome.md b/website/docs/resources/slides/lecture-welcome.md index 87ca512..905dd45 100644 --- a/website/docs/resources/slides/lecture-welcome.md +++ b/website/docs/resources/slides/lecture-welcome.md @@ -1,7 +1,7 @@ --- -author: Topics in Security and Privacy Technologies (CS 839) +author: Security and Privacy in Data Science (CS 763) title: Course Welcome -date: September 05, 2018 +date: September 04, 2019 --- # Security and Privacy @@ -41,76 +41,142 @@ date: September 05, 2018 - Automatically check security properties - Search for attacks and vulnerabilities -## Our focus: four modules +## Five modules 1. Differential privacy -2. Applied cryptography -3. Language-based security -4. Adversarial machine learning +2. Adversarial machine learning +3. Applied cryptography +4. Algorithmic fairness +5. PL and verification + +## This course is broad! +- Each module could be its own course + - We won't be able to go super deep + - You will probably get lost +- Our goal: broad survey of multiple areas + - Lightning tour, focus on high points + +> Hope: find a few things that interest you + +## This course is technical! +- Approach each topic from a rigorous point of view +- Parts of "data science" with **provable guarantees** +- This is not a "theory course", but... + +. . . + +![](images/there-will-be-math.png) # Differential privacy +## + +![](images/privacy.png) + ## A mathematically solid definition of privacy - Simple and clean formal property - Satisfied by many algorithms - Degrades gracefully under composition -# Applied crypto - -## Computing in an untrusted world -- Proving you know something without revealing it -- Certifying that you did a computation correctly -- Computing on encrypted data, without decryption -- Computing joint answer without revealing your data - -# Language-based security - -## Ensure security by construction -- Programming languages for security -- Compiler checks that programs are secure -- Information flow, privacy, cryptography, ... - # Adversarial machine learning +## + +![](images/aml.jpg) + ## Manipulating ML systems - Crafting examples to fool ML systems - Messing with training data - Extracting training information +# Applied crypto + +## + +![](images/crypto-ml.png) + +## Crypto in data science +- Learning models without raw access to private data +- Collecting analytics data privately, at scale +- Side channels and implementation issues +- Verifiable execution of ML models +- Other topics (e.g., model watermarking) + +# Algorithmic fairness + +## + +![](images/fairness.png) + +## When is a program "fair"? +- Individual and group fairness +- Inherent tradeoffs and challenges +- Fairness in unsupervised learning +- Fairness and causal inference + +# PL and verification + +## + +![](images/pl-verif.png) + +## Proving correctness +- Programming languages for security and privacy +- Interpreting neural networks and ML models +- Verifying properties of neural networks +- Verifying probabilistic programs + # Tedious course details +## Lecture schedule +- First ten weeks: **lectures MWF** + - Intensive lectures, get you up to speed + - M: I will present + - WF: You will present +- Last five weeks: **no lectures** + - Intensive work on projects + - I will be available to meet, one-on-one + +> You must attend lectures and participate + ## Class format - Three components: 1. Paper presentations - 2. Final project - 3. Class participation -- Annoucement/schedule/materials: on [website](https://pages.cs.wisc.edu/~justhsu/teaching/current/cs839/) -- Class mailing list: [compsci839-1-f18@lists.wisc.edu]() + 2. Presentation summaries + 3. Final project +- Announcement/schedule/materials: on [website](https://pages.cs.wisc.edu/~justhsu/teaching/current/cs763/) +- Class mailing list: [compsci763-1-f19@lists.wisc.edu]() ## Paper presentations -- Sign up to lead a discussion on one paper -- Suggested topic, papers, and schedule on website -- Before each presentation: - - I will send out brief questions - - Please email me brief answers +- In pairs, lead a discussion on group of papers + - See website for [detailed instructions](https://pages.cs.wisc.edu/~justhsu/teaching/current/cs763/assignments/presentations/jjj) + - See website for [schedule of topics](https://pages.cs.wisc.edu/~justhsu/teaching/current/cs763/schedule/lectures/) +- One week **before** presentation: meet with me + - Come prepared with presentation materials + - Run through your outline, I will give feedback -> If you want advice, come talk to me! +## Presentation summaries +- In pairs, prepare written summary of another group + - See website for [detailed instructions](https://pages.cs.wisc.edu/~justhsu/teaching/current/cs763/assignments/summaries/) + - See website for [schedule of topics](https://pages.cs.wisc.edu/~justhsu/teaching/current/cs763/schedule/lectures/) +- One week **after** presentation: send me summary + - I will work with you to polish report + - Writeups will be shared with the class ## Final project -- Work individually or in pairs -- Project details and suggestions on website +- In groups of three (or very rarely two) +- See website for [project details](https://pages.cs.wisc.edu/~justhsu/teaching/current/cs763/assignments/project/) - Key dates: - - **September 19**: Pick groups and topic - - **October 15**: Milestone 1 - - **November 14**: Milestone 2 + - **September 9**: Form groups, pick topic + - **October 11**: Milestone 1 + - **November 8**: Milestone 2 - **End of class**: Final writeups and presentations -> If you want advice, come talk to me! - ## Todos for you -0. Complete the course survey -1. Check out the course website -2. Think about what paper you want to present -3. Brainstorm project topics +0. Complete the [course survey](https://forms.gle/NvYx3BM7HVkuzYdG6) +1. Explore the [course website](https://pages.cs.wisc.edu/~justhsu/teaching/current/cs763/) +2. Think about which lecture you want to present +3. Think about which lecture you want to summarize +4. Brainstorm project topics # Defining privacy