The School of Computing and Data Science (https://www.cds.hku.hk/) was established by the University of Hong Kong on 1 July 2024, comprising the Department of Computer Science and Department of Statistics and Actuarial Science and Department of AI and Data Science.

Courses Offered

COMP3523 Security and Privacy in Artificial Intelligence

COMP3523 Security and Privacy in Artificial Intelligence

2025-26
Instructor(s):Chen Ho
(Class A) No. of credit(s):6
Recommended Learning Hours:
Lecture: 36.0
Tutorial: 3.0
Pre-requisite(s):COMP3314
Co-requisite(s):  
Mutually exclusive with:  
Remarks:

Course Learning Outcomes

1. [Foundation]
Be able to understand the principles and objectives of the security and privacy of artificial intelligence.
2. [Model]
Be able to understand AI security models and to apply the model to achieve the security objectives.
3. [Design]
Be able to understand the basic principles of AI security design and to apply the principles.
4. [Application]
Be able to understand the security issues of practical AI systems.
5. [Application development]
Be able to implement practical AI systems in a secure manner.
Mapping from Course Learning Outcomes to Programme Learning Outcomes
 PLO aPLO bPLO cPLO dPLO ePLO fPLO gPLO hPLO iPLO j
CLO 1T,PT,PT,P
CLO 2T,PT,PT,P
CLO 3T,PT,PT,PT,P
CLO 4T,PT,PT,PT,P
CLO 5T,PT,PT,PT,P

T - Teach, P - Practice
For BEng(CompSc) Programme Learning Outcomes, please refer to here.

Syllabus

Calendar Entry:
This course will equip students with the knowledge and hands-on experience to develop secure, privacy-preserving AI systems. As AI becomes increasingly integrated into our everyday lives, students will explore how seemingly powerful AI systems can be compromised through various attacks that manipulate decision-making processes and steal private information. Students will also learn about cutting-edge defenses designed to protect these systems. By the end of the course, students will be able to assess security and privacy risks when designing AI-driven solutions and implement effective countermeasures.

Detailed Description:

Introduction to security and privacy Mapped to CLOs
Introduction to security and privacy1, 2
Introduction to machine learning Mapped to CLOs
Introduction to machine learning2, 3
Security and privacy in CNN Mapped to CLOs
Security and privacy in CNN2, 3
Security and privacy in LLM Mapped to CLOs
Security and privacy in LLM4, 5
Security and privacy in AI agents Mapped to CLOs
Security and privacy in AI agents4, 5

Assessment:
Continuous Assessment: 50%
Written Examination: 50%

Teaching Plan

Please refer to the corresponding Moodle course.

Moodle Course(s)

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