Notes for previous version CS 839.

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Security and Privacy are emerging as very important research areas.
Vulnerabilities in software are found and exploited almost everyday
and with disastrous 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 investigate techniques to make software more secure.
Techniques for ensuring privacy of sensitive data will also be
covered. Adversarial ML (what happens to ML algorithms in the
presence of adversaries?) will be also be discussed. List of some
topics that we will cover (obviously not complete) are given below.
Software Security:
- Information flow
- Techniques for finding vulnerabilities in software
- Defense techniques (e.g., control-flow integrity)
Privacy:
- Differential Privacy
- Zero-knowledge proofs
- Secure multi-party computation
Adversarial ML:
- Training-time attacks
- Test-time attacks
- Model Theft attacks
Grading: There are three components that relate to grading:
- Reading research papers and writing reviews.
- Few homeworks.
- Class project.