Published Nov 20, 2024
Evolution of computer security. Types of security threats, hardware threats, software threats, physical threats, cryptanalysis. The theory of secure message passing. Methods of encryption, private networks, Data Encryption Standard, Public Key Cryptosystems. Secrecy and Privacy in a network environment, long haul networks, local area networks. Protocols for computer network security.
This course focuses on the fundamental principles of computer network security. The topics to be covered include practical symmetric-key and public-key cryptographic schemes, semantic security, network and wireless security, detection of relay attacks, multicast security, trusted platform, tamper resistant hardware, decentralized system security, blockchain and cryptocurrency, zero-knowledge proofs, blockchain privacy, privacy enhanced technologies, secure machine learning, post-quantum cryptography and quantum key distribution.
| Explain foundational principles of computer network security, including confidentiality, integrity, authentication, trust models, and attack types. |
| Analyze and implement symmetric and public-key cryptographic schemes, including advanced techniques and their vulnerabilities |
| Evaluate and apply security protocols for networks, wireless systems, and multicast communications, addressing common attacks. |
| Develop secure solutions using trusted platforms, tamper-resistant hardware, and countermeasures for physical attacks. |
| Address security challenges in decentralized systems, including blockchain, cryptocurrencies, and smart contracts. |
| Acquire practical experience with emerging technologies such secure machine learning and future technology of quantum cryptography. |
| Build a strong foundation for research or professional work in the field of computer network security. |
Chapter 1. Basics of Computer Network Security
Chapter 2. Cryptographic Fundamentals
Chapter 3. Network and Wireless Security
Chapter 4. Multicast Security
Chapter 5. Trusted Platform and Hardware Security
Chapter 6. Decentralized System Security
Chapter 7. Zero knowledge proofs and blockchain privacy
Chapter 8. Privacy Enhanced Technologies
Chapter 9. Post‐quantum and Quantum Cryptography
Note: Any prices provided in course outlines are best estimates based on recent online prices and do not include shipping or taxes. Prices may vary between retailers.
There is no textbook for the course, but the following references will be helpful for your reading.
| Component | Value |
|---|---|
| Midterm Examination | 30% |
| Project (both slides and report) due on March 28 | 30% |
| Final Examination | 40% |
The overall grade is based on a midterm exam (take-home exam), one project (individual or 2-person group) and one final exam (open book exam, but only lecture slides are allowed to bring). For the project, a list of the project problems will be provided. A 5-8 minutes presentation slides and a report of 5-10 pages in an academic research article format are a must to obtain the score for the project. The distribution of the marks are shown above.
Text matching software (Turnitin) will be used to screen assignments in this course. This is being done to verify that use of all material and sources in assignments is documented. In the first week of the term, details will be provided about the arrangements for the use of Turnitin and alternatives in this course. See Administrative Policy below for more information and links.
Generative artificial intelligence (GenAI) trained using large language models (LLM) or other methods to produce text, images, music, or code, like Chat GPT, DALL-E, or GitHub CoPilot, may be used for assignments in this class with proper documentation, citation, and acknowledgement. Recommendations for how to cite GenAI in student work at the University of Waterloo may be found through the Library: https://subjectguides.uwaterloo.ca/chatgpt_generative_ai. Please be aware that generative AI is known to falsify references to other work and may fabricate facts and inaccurately express ideas. GenAI generates content based on the input of other human authors and may therefore contain inaccuracies or reflect biases.
In addition, you should be aware that the legal/copyright status of generative AI inputs and outputs is unclear. Exercise caution when using large portions of content from AI sources, especially images. More information is available from the Copyright Advisory Committee: https://uwaterloo.ca/copyright-at-waterloo/teaching/generative-artificial-intelligence
You are accountable for the content and accuracy of all work you submit in this class, including any supported by generative AI.
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 for more information.]
Grievance: A student who believes that a decision affecting some aspect of their 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 an academic offence, and to take responsibility for their actions. [Check the Office of Academic Integrity for more information.] A student who is unsure whether an action constitutes an offence, or who needs help in learning how to avoid offences (e.g., plagiarism, cheating) or about “rules” for group work/collaboration should seek guidance from the course instructor, academic advisor, or the undergraduate associate dean. For information on categories of offences and types of penalties, students should refer to Policy 71, Student Discipline. For typical penalties, check Guidelines for the Assessment of Penalties.
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 they have 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 Services at the beginning of each academic term.
Turnitin.com: Text matching software (Turnitin®) may be used to screen assignments in this course. Turnitin® is used to verify that all materials and sources in assignments are documented. Students' submissions are stored on a U.S. server, therefore students must be given an alternative (e.g., scaffolded assignment or annotated bibliography), if they are concerned about their privacy and/or security. Students will be given due notice, in the first week of the term and/or at the time assignment details are provided, about arrangements and alternatives for the use of Turnitin in this course.
It is the responsibility of the student to notify the instructor if they, in the first week of term or at the time assignment details are provided, wish to submit alternate assignment.