Security and Privacy

Recommended Prerequisites

Programming, basic skills on Databases, Networks and Information Systems.

Teaching Methods

Lecture classes (T): presentation and discussion around the topics of the course.
Lab classes (PL): application of theoretical concepts in projects.

Learning Outcomes

This course provides a comprehensive understanding of privacy principles and techniques for safeguarding privacy across the data life cycle. Students will master fundamental security concepts focused on privacy and the tools necessary for developing applications that handle sensitive data. Emphasis is placed on privacy issues, including the ethical and legal obligations of organizations. Key techniques for protecting data privacy in storage, communication, and processing will be covered, including i) privacy-preserving principles for data publication, ii) secure multiparty computation, iii) anonymous authentication, iv) location privacy, v) secure search over encrypted data, vi) the intersection of privacy and AI, and vii) homomorphic encryption for privacy.

Work Placement(s)

No

Syllabus

Topic 1: Fundamentals of Privacy and Security

Topic 2: Privacy Preserving Data Publishing

Topic 3: Secure Multiparty Computation

Topic 4: Anonymous Authentication

Topic 5: Digital Footprint Management

Topic 6: Location Privacy

Topic 7: Searchable Encryption

Topic 8: Privacy Preserving AI

Topic 9: Synthetic Data Generation

Topic 10: Adversarial Machine Learning and Privacy

Topic 11: Privacy Through Homomorphic Encryption

Topic 12: Emerging Related Controversial Topics (e.g., Post-Quantum Encryption, AI for Cybersecurity.

Head Lecturer(s)

Naghmeh Ramezani Ivaki

Assessment Methods

Assessment
Project: 50.0%
Exam: 50.0%

Bibliography

• - Security in Computing - Charles Pfleeger, et al., Prentice Hall, 6th Ed., 2023.

-Computer Security: Principles and Practice - William Stallings et al., Pearson, 5th Ed., 2023.

-Information Security: Principles and Practice - Mark Stamp, Wiley, 3rd Ed., 2021.

-Privacy-Preserving Data Publishing - Raymond Chi-Wing Wong et al., Springer, 2022.

-Network Security Essentials - William Stallings, 6th Ed., 2021.

-Cryptography and Network Security - William Stallings, 5th Ed., 2023.

-Introduction to Modern Cryptography - Jonathan Katz et al., CRC Press, 3rd Ed., 2020.

-Privacy-Preserving Computing for Big Data and AI - Kai Chen, Qiang Yang, 1st Ed., 2024.

-Secure Multi-Party Computation - Ashish Choudhury et al., Springer, 2022.

-Searchable Encryption - Kui Ren et al., Springer, 2023.

-Protecting Privacy through Homomorphic Encryption - Kristin Lauter, et al., Springer, 2022.

-Location Privacy: A Comparative Overview - Kostantinos Chatzikokolakis et al., Now Publishers, 2017