CS 489/698 - Privacy, Crypto, Network, Data Security
Spring 2024

Syllabus

Note that all times for this course are specified in Eastern Time (the timezone of Waterloo and Toronto).

Course Description

This course provides an introduction to data privacy and security, using cryptography and related techniques in networks, distributed systems, and data science. It examines how data and meta-data can be protected at rest, in transit, and during computation. Students completing this course should be able to use and deploy data security and privacy protection technologies in networks and (distributed) data science environments. In layman terms, this course shows you how to benefit from the Internet and machine learning and still preserve individuals' privacy.

• • Evaluate the use of cryptography to protect data assets in storage, transit, and use
• • Analyze security and privacy threats to data assets, including the privacy level of various data release mechanisms, privacy-utility trade-offs, and statistical inference attacks to infer sensitive information
• • Evaluate the use of network security hardware and software to protect data assets in transit and use.
• • Compare various network security mechanisms, and articulate their advantages and limitations.

Course Outline

• • Intro security/privacy
• • Ethics/policy relevant to this course
• • Basics of cryptography
• • Symmetric encryption
• • Hash functions, MAC
• • Public key encryption (RSA)
• • Semantic security, etc.

• • Network Security Primer: Firewalls, Intrusion Detection, Honeypots
• • Authentication Failures: Spoofs (IP, user ids), rerouting attacks (DNS, etc.)
• • Authentication Primer (Needham-Schroeder/Kerberos, SAML, etc.), PAKE
• • PKI, DH, DNSSEC
• • Confidentiality Failures: Snooping, Web tracking (cookies), browser fingerprinting
• • TLS, VPN, WPA2
• • Tor, Mixes, Secure email and messaging (Signal, PGP, etc.)
• • Traffic analysis
• • Network covert channels

• • Data Security: Inference attacks (leakage from function output, background information, side channels)
• • k-Anonymity, l-diversity, (t-plausibility)
• • Differential privacy (Laplace, etc.)
• • Private machine learning
• • Homomorphic encryption
• • Intro to MPC, PSI, PIR

Grading Scheme

Grades for this course will be calculated as follows:

For graduate students: the above scaled to 80% + 20% survey paper

Midterms: We will have each midterm in person, during class. These midterms are written-only (no programming) but may cover any material taught until each midterm's date. Final grades will be available after the end of term through LEARN.

Assignments:

The three assignments are meant to be completed individually. The assignments are based on a mix of theory (written) and practical (programming) exercises. Students will leverage the knowledge and techniques presented in the lectures for completing the assignments.

The assignments are due at 3:00 pm Eastern Time on their respective due dates. Please start working on the assignments in advance of the deadlines. Late submissions for Assignments 1, 2, and 3 will be accepted only up to 48 hours after the original due date. There is no penalty for accepted late submissions. Assignments can be submitted multiple times, and the last one will be used for marking. Course personnel will not give assistance for assignments after their original due dates, so you are encouraged to respect the due date.

Remarking Policy:

If you have an assignment that you would like to have reappraised, please follow the instructions given on LEARN to submit your request. Include a clear justification for your claims. The appeals deadline is one week after the respective graded item is first made available. If your appeal is concerned with a simple calculation error, please see the TA(s) during their office hours.

Research Survey Paper (CS 689):

Students registered in CS 689 must write a research survey paper on a topic related to data security or privacy. In writing your paper, you must become familiar with the research literature relevant to your topic. Your focus should be on academic venues, such as the USENIX Security Symposium, ACM CCS, IEEE Symposium on Security and Privacy, Privacy Enhancing Technologies Symposium (PETS), or the NDSS Symposium.

Your topic must be approved in advance by the instructors before you submit your full survey at the end of term. Your proposal should be one page in length and include at least 10 references, preferably including (but not limited to) papers from the aforementioned venues. Email your proposal to the instructors by June 12th.

Your paper should be a summary of past and current work on your topic, as well as an overview of known open problems and potential future directions in the area. You should provide a concise summary of work, emphasizing major accomplishments, rather than a detailed accounting of individual pieces of research activity. Email your final paper to the instructors by July 31st.

Your proposal and paper paper should be formatted in the two-column ACM proceedings format, using one of the ACM SIG Proceedings Templates. Your paper should not be longer than six pages. The ACM templates include headings for “Categories and Subject Descriptors”, “General Terms”, and “Keywords”, which you do not need to use.

Textbooks

Communication

Please direct all communication to the Piazza discussion forum. This includes questions about materials in lectures, assignments, and general logistics.
It is your responsibility to keep up with all course-related information posted to LEARN, the course Piazza forum, and the course website.

Etiquette:

Email:

General University Policy

• Academic Integrity: In order to maintain a culture of academic integrity, members of the University of Waterloo community are expected to promote honesty, trust, fairness, respect and responsibility. Check the Office of Academic Integrity's website for more information.

  All members of the UW community are expected to hold to the highest standard of academic integrity in their studies, teaching, and research. This site explains why academic integrity is important and how students can avoid academic misconduct. It also identifies resources available on campus for students and faculty to help achieve academic integrity in — and out — of the classroom.

• Grievance: A student who believes that a decision affecting some aspect of his/her university life has been unfair or unreasonable may have grounds for initiating a grievance. Read Policy 70 — Student Petitions and Grievances, Section 4. When in doubt please be certain to contact the department's administrative assistant who will provide further assistance.

• Discipline: A student is expected to know what constitutes academic integrity, to avoid committing academic offenses, and to take responsibility for his/her actions. Check the Office of Academic Integrity for more information. A student who is unsure whether an action constitutes an offense, or who needs help in learning how to avoid offenses (e.g., plagiarism, cheating) or about "rules" for group work/collaboration should seek guidance from the course professor, academic advisor, or the Undergraduate Associate Dean. For information on categories of offenses and types of penalties, students should refer to Policy 71 — Student Discipline. For typical penalties, check Guidelines for the Assessment of Penalties.

• Avoiding Academic Offenses: Most students are unaware of the line between acceptable and unacceptable academic behaviour, especially when discussing assignments with classmates and using the work of other students. For information on commonly misunderstood academic offenses and how to avoid them, students should refer to the Office of Academic Integrity's site on Academic Misconduct and the Faculty of Mathematics Cheating and Student Academic Discipline Policy.

• Appeals: A decision made or penalty imposed under Policy 70, Student Petitions and Grievances (other than a petition) or Policy 71, Student Discipline may be appealed if there is a ground. A student who believes he/she has a ground for an appeal should refer to Policy 72, Student Appeals.

Note for Students with Disabilities

AccessAbility Services, located in Needles Hall, Room 1401, collaborates with all academic departments to arrange appropriate accommodations for students with disabilities without compromising the academic integrity of the curriculum. If you require academic accommodations to lessen the impact of your disability, please register with AccessAbility at the beginning of each academic term.

Coronavirus Information and Resources

• Library COVID-19: Updates on library services and operations
• Coronavirus Information for Students This resource provides updated information on COVID-19 and guidance for accommodations due to COVID-19.

Mental Health Support

All of us need a support system. We encourage you to seek out mental health supports when they are needed. Please reach out to Campus Wellness and Counselling Services.
We understand that these circumstances can be troubling, and you may need to speak with someone for emotional support. Good2Talk is a post-secondary student helpline based in Ontario, Canada that is available to all students.

Territorial Acknowledgement

We acknowledge that we live and work on the traditional territory of the Attawandaron (Neutral), Anishinaabeg, and Haudenosaunee peoples. The University of Waterloo is situated on the Haldimand Tract, the land promised to the Six Nations that includes ten kilometres on each side of the Grand River.