Graduate Courses

Basic concepts of computer security and the theory and current practices of authentication, authorization, and privacy mechanisms in modern operating systems and networks.

Not offered on a regular basis.

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Examination of security and privacy issues related to protecting personal data in various environments (for example: cloud computing, smart grid, and internet of things) cover the fundamentals and principles of data security and privacy, and computational and statistical techniques for…

The principles and practice of computer forensics. Topics include computer crime, software vulnerabilities, intellectual property, privacy issues, countermeasures, methods and standards for extraction, preservation, and deposition of legal evidence in a court of law.

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Applied research project under the direction of the major professor for the Computer Science Non-thesis MS degree. As part of the requirements, a comprehensive report must be prepared detailing the student's procedures and findings regarding the completed project work.

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Students will learn and discuss the most significant research that has led to creating cloud computing, as well as new research that will soon be reflected in real-world clouds. Topics include the concept of basic cloud computing (e.g., virtualization, data centers, elastic resource management…

Exploration of both the foundation and recent advances in software security and cyber forensics. Topics will include software vulnerability analysis, advanced attack and defense techniques, cybercrime investigation and forensics, and security and forensics in different platforms (e.g., mobile,…

Our core software stacks are built upon unsafe language (e.g. C/C++). However, with the progress of safe languages, such as Rust and Go, industries are rewriting legacy codes to make our systems safer. In this course, students will learn about security concerns related to unsafe language and…

Recent advances in computer networks and system security. Fast and secure network systems, secure storage systems, high performance intrusion detection systems, and efficient anti-abuse systems.

Not offered on a regular basis.

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This is an advanced course on computer and network security. The course will mainly focus on reading and analyzing recent top- tier research publications in the field of computer security and privacy and on the research and development of systems that can enforce security and privacy in the real…

An introduction to technologies that support building trustworthy machine learning systems. Topics include, but are not limited to, adversarial machine learning, privacy-preserving machine learning, transparency in machine learning, and fairness of machine learning.

An introduction to the privacy preservation problems, as well as algorithmic and statistical techniques for data privacy, in modern data analysis, such as machine learning and data mining. Approaches include randomized algorithms, synthetic data generation, stability analysis, and so on.

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Introduction to security problems associated with the emerging Internet of Things (IoT) technologies, including privacy disclosure and data manipulation. Topics studied include architectural differences leading to such issues, how adversaries launch attacks by either exploiting software…