For more details on the courses, please refer to the Course Catalog
| Code | Course Title | Credit | Learning Time | Division | Degree | Grade | Note | Language | Availability |
|---|---|---|---|---|---|---|---|---|---|
| ESW5053 | Introduction to Digital Forensics | 3 | 6 | Major | Master/Doctor | 1-4 | - | No | |
| Digital forensics uses digital data embedded in information devices as a basis and uses the information devices as a medium. This is a security service field that identifies and proves the facts of any action that occurred. In this subject, in the process of collecting evidence and analyzing evidence, which are digital forensic procedures, we will take a look at the necessary technologies and problems. We also look at the current status, application areas, and development direction. Digital forensic technology varies greatly depending on the security system of the operating system installed on the information device. We focus on learning Windows, a representative desktop operating system, and Android, a mobile operating system. | |||||||||
| ESW5054 | Security Topics in Memory Hierarchy | 3 | 6 | Major | Master/Doctor | 1-4 | - | No | |
| In this course, we will explore the security threats that can arise in the memory hierarchy and memory interfaces of modern computer systems, as well as the defensive techniques against these threats. The course begins with the basic principles of memory hierarchy structure, covering various types of memory such as cache memory, main memory, and secondary storage. Additionally, we study the importance of memory security, the related threats, and the techniques and methodologies to protect systems from these threats. Students will understand memory-related attack techniques, for example, buffer overflow and cache side-channel attacks, and will also learn about the security threats associated with modern memory interfaces like CXL (Compute Express Link). | |||||||||
| ESW5055 | Secure Programming Using LLM | 3 | 6 | Major | Master/Doctor | 1-4 | - | No | |
| This course is centered on learning and practicing secure programming techniques using Large Language Models (LLMs). Students will study the fundamental concepts, operating principles, and applications of LLMs in the field of programming. The course covers topics such as code generation, bug detection and fixing, and security vulnerability analysis. Through hands-on projects, students will learn how to write more secure and efficient code using LLMs and leverage their capabilities to solve security-related issues. The course explores effective ways to integrate LLMs into security programming, keeping pace with the latest technological trends. | |||||||||
| ESW5056 | Hands-on Security | 3 | 6 | Major | Master/Doctor | 1-4 | - | No | |
| This course focuses on a wide range of hands-on security topics, learning by getting one’s hands dirty. In particular, students should be able to understand how a theoretical concept applies real system, network, or application in practice. Each class, a student will learn a core concept, prepare a setup for the hands-on lab, and perform a specific attack/defense. The topics include (but not limited to) system security, network security, software security, hardware security, web security, and cryptography. | |||||||||
| ESW5057 | Computational Logic | 3 | 6 | Major | Master/Doctor | 1-4 | - | No | |
| In this course ‘Computational Logic’, we will explore computational logic, which is a logic used for reasoning about program behavior. This lecture will cover program verification techniques for proving that programs meet their specification. Specifically, we will delve into propositional logic, first-order logic, first-order theories, program verification, and more. Another objective of this lecture is to read and discuss research papers related to program verification, analysis, and debugging. | |||||||||
| ESW7001 | ICT Standard Technologies and Practice | 3 | 6 | Major | Bachelor/Master/Doctor | 1-4 | Korean | Yes | |
| This course aims at introducing ICT standard technologies to students, and letting them acquire the standard technologies by writing a standard draft. The ICT standard technologies include Artificial Intelligence (AI) and Networks, Smart Health, Satellite Communications, Internet of Things (IoT), Software-Defined Networking (SDN), Network Functions Virtualization (NFV), and Intent-Based Networking (IBN). It explains the introduction to ICT standardization, international standard technologies, detailed technologies per Standards Developing Organizations (SDOs), and international standardization strategies. The students can experience the process of developing a standard technology by writing a standard draft as a term project. The SDOs include 3GPP (3rd Generation Partnership Project) for the standardization of cellular networks and IETF (Internet Engineering Task Force) for the standardization of the Internet. | |||||||||
| ESW7002 | Data Modeling for Intelligent Networks and Security | 3 | 6 | Major | Bachelor/Master/Doctor | 1-4 | English | Yes | |
| This course aims at the teaching of Data Modeling and Management Automation for Intelligent Networks and Security. For various services in Software-Defined Networking (SDN) and Network Functions Virtualization (NFV), it explains YANG Data Modeling Language that has been developed by IETF (Internet Engineering Task Force) that is the Internet Standardization Organization. Remote control for management automation uses NETCONF and RESTCONF protocols. This course deals with YANG data models for the management automation of intelligent networks and security. Policies and rules on the networks and security can be constructed by the YANG data models that generate XML documents. These XML documents can be delivered to a server (i.e., network or security system) by a client (or administrator) to configure the policies and rules on the target server via NETCONF or RESTCONF. As an example for network security management automation, this course uses the framework and interfaces of Interface to Network Security Functions (I2NSF) in IETF. Through Intent-Based Networking (IBN), this course explains a security policy translator to automatically translate a high-level security policy into the low-level security policy for the requested network security services. | |||||||||
| FIT5003 | Financial Statistics | 3 | 6 | Major | Master/Doctor | FinTech | Korean | Yes | |
| This course covers an introductory level of probability and statistical analysis for graduate students who major in finance. We emphasize topics of probability and statistical theories that students will encounter in graduate finance and econometric courses. Topics include probability theory, sampling, statistical estimation, and hypothesis testing. | |||||||||
| FIT5005 | AI & Wealth Management | 3 | 6 | Major | Master/Doctor | FinTech | English | Yes | |
| This is a course in AI & Wealth Management for FinTech Master or Ph.D. program.This is a course in AI & Wealth Management for FinTech Master or Ph.D. program.This is a course in AI & Wealth Management for FinTech Master or Ph.D. program.This is a course in AI & Wealth Management for FinTech Master or Ph.D. program.This is a course in AI & Wealth Management for FinTech Master or Ph.D. program.This is a course in AI & Wealth Management for FinTech Master or Ph.D. program.This is a course in AI & Wealth Management for FinTech Master or Ph.D. program. | |||||||||
| FIT5006 | Blockchain & Financial Application | 3 | 6 | Major | Master/Doctor | FinTech | Korean | Yes | |
| This is a course in Blockchain & Financial Application for FinTech Master or Ph.D. program.This is a course in Blockchain & Financial Application for FinTech Master or Ph.D. program.This is a course in Blockchain & Financial Application for FinTech Master or Ph.D. program.This is a course in Blockchain & Financial Application for FinTech Master or Ph.D. program. | |||||||||
| FIT5007 | AI Financial Application | 3 | 6 | Major | Master/Doctor | FinTech | - | No | |
| This is a course in AI Financial Application for FinTech Master or Ph.D. program.This is a course in AI Financial Application for FinTech Master or Ph.D. program.This is a course in AI Financial Application for FinTech Master or Ph.D. program. | |||||||||
| FIT5011 | AI Financial Data Market Analysis | 3 | 6 | Major | Master/Doctor | FinTech | - | No | |
| This is a course in AI Financial Data Market Analysis for FinTech Master or Ph.D. program.This is a course in AI Financial Data Market Analysis for FinTech Master or Ph.D. program.This is a course in AI Financial Data Market Analysis for FinTech Master or Ph.D. program.This is a course in AI Financial Data Market Analysis for FinTech Master or Ph.D. program. | |||||||||
| FIT5012 | RegTech | 3 | 6 | Major | Master/Doctor | FinTech | - | No | |
| This is a course in RegTech for FinTech Master or Ph.D. program. This is a course in RegTech for FinTech Master or Ph.D. program. This is a course in RegTech for FinTech Master or Ph.D. program. This is a course in RegTech for FinTech Master or Ph.D. program. This is a course in RegTech for FinTech Master or Ph.D. program. | |||||||||
| FIT5013 | AI Financial Platform | 3 | 6 | Major | Master/Doctor | FinTech | - | No | |
| This is a course in AI Financial Platform for FinTech Master or Ph.D. program.This is a course in AI Financial Platform for FinTech Master or Ph.D. program.This is a course in AI Financial Platform for FinTech Master or Ph.D. program.This is a course in AI Financial Platform for FinTech Master or Ph.D. program.This is a course in AI Financial Platform for FinTech Master or Ph.D. program.This is a course in AI Financial Platform for FinTech Master or Ph.D. program. | |||||||||
| FIT5015 | FinTech Marketing Issue | 3 | 6 | Major | Master/Doctor | FinTech | - | No | |
| This is a course in FinTech Marketing Issue for FinTech Master or Ph.D. program.This is a course in FinTech Marketing Issue for FinTech Master or Ph.D. program.This is a course in FinTech Marketing Issue for FinTech Master or Ph.D. program.This is a course in FinTech Marketing Issue for FinTech Master or Ph.D. program.This is a course in FinTech Marketing Issue for FinTech Master or Ph.D. program. | |||||||||