32 lines
1.1 KiB
Markdown
32 lines
1.1 KiB
Markdown
*Security and privacy* are rapidly emerging as critical research areas in
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computer science and beyond. Vulnerabilities in software are found and exploited
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almost everyday, with grave consequences. Personal data today is aggregated at
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large scales, increasing the risk of privacy violations or breaches. Finally,
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*machine-learning* (ML) algorithms are seeing real-world applications in
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critical sectors (e.g., health care, automation, and finance), but their
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behavior in the presence of malicious adversaries is poorly understood.
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This advanced topics class will cover recent techniques from the frontiers of
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security and privacy research. Topics will be drawn from the following broad
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areas, depending on student interest:
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### Differential Privacy
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- Basic properties and examples
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- Advanced mechanisms
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- Local differential privacy
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### Cryptographic Techniques
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- Zero-knowledge proofs
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- Secure multi-party computation
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- Verifiable computation
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### Language-Based Security
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- Secure information flow
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- Differential privacy
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- Symbolic cryptography
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### Adversarial Machine Learning
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- Training-time attacks
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- Test-time attacks
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- Model-theft attacks
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