38 lines
1.8 KiB
Markdown
38 lines
1.8 KiB
Markdown
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# Lecture Schedule (Tentative)
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Date | Topic | Presenter
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9/5 | Course welcome | JH
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| <center> **Differential Privacy** </center> |
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9/10 | Definition and Basic Mechanisms | JH
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9/12 | What does Differential Privacy mean? | JH
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9/17 | Composition and closure properties | JH
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9/19 | Exponential mechanism <br> **Paper:** | JH
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9/24 | Streaming privacy: counters <br> **Paper:** | JH
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9/26 | Advanced mechanisms: Report-noisy-max | JH
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10/1 | Advanced mechanisms: Sparse Vector | JH
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10/3 | Advanced mechanisms: Private multiplicative weights <br> **Paper:** | JH
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10/8 | Local differential privacy (theory) | JH
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10/10 | Local differential privacy (practice) <br> **Paper:** | JH
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| <center> **Cryptographic Techniques** </center> |
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10/15 | Crypto: overview and basics | JH
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10/17 | Zero-knowledge proofs <br> **Paper:** |
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10/22 | Oblivious transfer and SMC <br> **Paper:** |
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10/24 | Oblivious transfer and SMC <br> **Paper:** |
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10/29 | Fully homomorphic encryption and verifiable computing <br> **Paper:** |
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10/31 | Fully homomorphic encryption and verifiable computing <br> **Paper:** |
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| <center> **Language-Based Security** </center> |
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11/5 | LangSec: overview and basics | JH
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11/7 | Secure Information Flow <br> **Paper:** |
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11/12 | Secure Information Flow <br> **Paper:** |
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11/14 | Languages for privacy <br> **Paper:** |
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11/19 | Languages for privacy <br> **Paper:** |
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11/21 | Symbolic cryptography <br> **Paper:** |
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| <center> **Adversarial Machine Learning** </center> |
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11/26 | AML: overview and basics | JH
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11/28 | Adversarial examples <br> **Paper:** |
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12/3 | Adversarial examples <br> **Paper:** |
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12/5 | Training-time attacks <br> **Paper:** |
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12/10 | Training-time attacks <br> **Paper:** |
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12/12 | Model-theft attacks <br> **Paper:** |
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