1.2 KiB
Syllabus
Security and Privacy are rapidly emerging as critical research areas. Vulnerabilities in software are found and exploited almost everyday and with increasingly serious consequences (e.g., the Equifax massive data breach). Moreover, our private data is increasingly at risk and thus techniques that enhance privacy of sensitive data (known as privacy-enhancing technologies (PETS)) are becoming increasingly important. Also, machine-learning (ML) is increasingly being utilized to make decisions in critical sectors (e.g., health care, automation, and finance). However, in deploying these algorithms presence of malicious adversaries is generally ignored.
This advanced topics class will tackle techniques related to all these themes. We will cover the following broad topics.
Differential Privacy
- Basic properties and examples
- Advanced mechanisms
- Local differential privacy
Cryptographic Techniques
- Zero-knowledge proofs
- Secure multi-party computation
- Verifiable computation
Language-Based Security
- Secure information flow
- Differential privacy
- Symbolic cryptography
Adversarial Machine Learning
- Training-time attacks
- Test-time attacks
- Model-theft attacks