For more details on the courses, please refer to the Course Catalog
| Code | Course Title | Credit | Learning Time | Division | Degree | Grade | Note | Language | Availability |
|---|---|---|---|---|---|---|---|---|---|
| ESW4008 | Data Science and Security | 3 | 6 | Major | Bachelor/Master | Computer Science and Engineering | - | No | |
| This course is to learn about the AI security and privacy. Additionally, we study the role of AI, data and data analytics for security and privacy applications. This course focuses on applications of AI, machine learning and big data analytics to various security and privacy problems, using various data analysis and AI techniques to solve challenging security and privacy issues. | |||||||||
| ESW4013 | Automated Software Analysis | 3 | 6 | Major | Bachelor/Master | Computer Science and Engineering | - | No | |
| The class teaches both foundation and practical aspects of automated software analysis, which is used by various research domains such as software engineering, program analysis, and security. Such techniques are also increasingly adopted in industries in order to automatically detect SW bugs and vulnerabilities before officially releasing the products. In this course, the foundation of automated software analysis techniques such as the theory of abstract interpretation, data-flow analysis, concolic testing, symbolic execution, fuzzing, and instrumentation will be introduced. Moreover, the recent research papers from top-tier conferences which utilizes such automated analysis techniques will be introduced in order to teach students how these techniques can be used to solve research problems. In addition, through assignments, students will design and implement practical software analysis tools that find bugs and verify software properties. After taking this course, students are able to: - Understand the foundation and practice of software analysis techniques, and - Able to detect SW bugs and vulnerabilities automatically, and - Could perform research on automated SW analysis | |||||||||
| ESW4014 | Principles of Reinforcement Learning | 3 | 6 | Major | Bachelor/Master | Computer Science and Engineering | Korean | Yes | |
| In this course, students learn the basic theory algorithm of Reinforcement Learning (RL) to find the optimal policy for a given environment. From basic reinforcement learning theories such as Markov Decision Process, Planning, and Q-learning to deep neural network-based reinforcement algorithms such as Value Function Approximations and Policy Gradient Methods. In addition, Model-based RL through estimating environments, Exploitation & Exploration Trade-off, and Inverse RL that mimics the behavior of experts are also covered. Basic knowledge of data structures, algorithms and machine learning is required to take this course. | |||||||||
| ESW5010 | Advanced Operating Systems | 3 | 6 | Major | Master/Doctor | 1-4 | Computer Science and Engineering | Korean | Yes |
| This course introduces the concepts, architectures, and functions of operating systems, and deeply discusses some major functions of operating systems, such as file systems, process management, processor management, memory management, and I/O management at the kernel level. In detail, core mechanisms of each function of the Unix and Linux kernel are introduced and discussed. With this course, the students will get the practical capabilities in designing and improving the operating system functions. | |||||||||
| ESW5012 | Topics in Real-Time Systems for Software Platforms | 3 | 6 | Major | Master/Doctor | 1-4 | Computer Science and Engineering | English | Yes |
| This course studies classic real-time systems' theories, and then investigates the-state-of-the-art issues of real-time systems towards supporting software platforms. First, fundamental scheduling theories are covered, including scheduling for the basic real-time task model in uniprocessor/ multiprocessor/cluster platforms, as well as that for the fork-join model and synchronization. Based on the theoretical background, up-to-date papers for real-time systems are studied so as to support software platforms. | |||||||||
| ESW5014 | Advanced Topics in Computer Graphics | 3 | 6 | Major | Master/Doctor | 1-4 | Computer Science and Engineering | - | No |
| This course covers fundamental theories, advanced techniques, and practice in computer graphics. The theories covered in this course include images, geometry, modeling, transformation, projection, shading, texture mapping, ray tracing, global illumination, and special effects. The course also includes practical techniques to implement the theories using graphics processors. | |||||||||
| ESW5023 | Text Mining and Analytics | 3 | 6 | Major | Master/Doctor | Computer Science and Engineering | - | No | |
| Text mining and analytics is the process of discovering hidden knowledge from text data. Basically, text mining involves text categorization, text clustering, concept/entity extraction, sentiment analysis, document summarization, and entity relation modeling. Text analysis involves information retrieval, lexical analysis for word frequency distributions, and information extraction. The essential goal is to turn text into data for analysis via natural language processing (NLP) and analytical methods. In this course, we will cover the major techniques for text mining and analytics to discover interesting patterns and to extract useful knowledge, based on statistical approaches. We will also implement text mining techniques using Python library. For prerequisite courses, I strongly recommend that you take basic computer programming, data structures, algorithms, data mining, and machine learning. | |||||||||
| ESW5025 | Infra Networks and Security | 3 | 6 | Major | Master/Doctor | Computer Science and Engineering | - | No | |
| This course introduces technologies and standards of infrastructure networks and security. This course explains the technologies of networks and applications in the network infrastructure (e.g., cloud, Internet of Things, and vehicular networks), and also the technologies of security and privacy in this infrastructure. The contents of this course are as follows. - Week 1: Introduction to Infra Networks and Security - Week 2: Internet and Computer Networks - Week 3: Software-Defined Networking (SDN) - Week 4: Network Functions Virtualization (NFV) - Week 5: OpenStack-Based Cloud Systems - Week 6: Cloud-Based Security Service Systems - Week 7: YANG-Based Data Modeling - Week 8: Term Project Proposal - Week 9: NETCONF-Based Network Management - Week 10: Internet-of-Things (IoT) Networking - Week 11: IoT Applications - Week 12: IoT Security - Week 13: Vehicular Networking - Week 14: Vehicular Network Applications and Security - Week 15: Term Project Presentation This course will be delivered in the format of a flipped class. It has four homeworks and one term project. | |||||||||
| ESW5026 | Advanced Operating Systems Design | 3 | 6 | Major | Master/Doctor | Computer Science and Engineering | - | No | |
| This course covers the design and implementation of the principal operating systems components, such as process management, memory management and file systems. Specifically, we will examine the technological advancement in operating systems design by dissecting the historically influential operating systems. In addition, we will explore the future directions of operating systems by investigating the key issues in the cutting-edge hardware and software technology. | |||||||||
| ESW5027 | Advanced Computer Architecture Design | 3 | 6 | Major | Master/Doctor | Computer Science and Engineering | - | No | |
| This course purses in-depth study on advanced computer architecture. The class topic includes computer performance measurement, advanced cache design, instruction-level parallelism, multi-core processor, virtual memory, and storage systems. | |||||||||
| ESW5028 | Principles of Database Systems | 3 | 6 | Major | Master/Doctor | Computer Science and Engineering | - | No | |
| This course covers the architecture and principles of modern database systems, including relational databases and key-value stores. Major topics include database system architecture, storage, index, query optimization, and transaction management, with a focus on the new design ideas for flash storage and non-volatile memory. | |||||||||
| ESW5029 | Advanced Topics in Software Engineering | 3 | 6 | Major | Master/Doctor | Computer Science and Engineering | Korean | Yes | |
| This course aims to provide an in-depth understanding of a variety of issues, particularly important issues in the software development process. For example, it enables in-depth learning by paying attention to one issue each semester among various issues such as architecture design, requirements engineering, software design, software testing, debugging, and project management. This course is an advanced course of the software engineering at the undergraduate. | |||||||||
| ESW5034 | Machine Learning Security and Robustness | 3 | 6 | Major | Master/Doctor | Computer Science and Engineering | English | Yes | |
| Machine Learning (ML) techniques have been rapidly adopted in various vital applications. However, ML-based systems are encountering several vulnerabilities, which are threatening the overall security of the system. Several research works have been conducted to identify and shed light on these learning models' fundamental security/privacy problems. Also, various proposals have been made to countermeasures or mitigate these vulnerabilities. Since many graduate students are machine learning practitioners, it is essential to not only develop new learning models, but also be aware of the potential adversarial attacks and the ways to protect the ML model against them. This course help students to learn about the recent cutting-edge attacks and defenses techniques from the adversarial ML domain. Also, the course covers several related topics such as fundamental security concepts, writing secure coding, software security best practices, and software validation approaches and principles. This course requires a good knowledge about machine learning including deep learning and python development to learn the course contents. | |||||||||
| ESW7001 | ICT Standard Technologies and Practice | 3 | 6 | Major | Bachelor/Master/Doctor | 1-4 | Computer Science and Engineering | 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 | Computer Science and Engineering | 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. | |||||||||