36 lines
1.2 KiB
Markdown
36 lines
1.2 KiB
Markdown
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# Syllabus
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Security and Privacy are rapidly emerging as critical research areas.
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Vulnerabilities in software are found and exploited almost everyday
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and with increasingly serious consequences (e.g., the Equifax massive data
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breach). Moreover, our private data is increasingly at risk and thus
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techniques that enhance privacy of sensitive data (known as
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privacy-enhancing technologies (PETS)) are becoming increasingly
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important. Also, machine-learning (ML) is increasingly being utilized to
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make decisions in critical sectors (e.g., health care, automation, and
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finance). However, in deploying these algorithms presence of malicious
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adversaries is generally ignored.
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This advanced topics class will tackle techniques related to all these
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themes. We will cover the following broad topics.
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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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