校際選修

115-1 選課時程

進行中

  • 初選第一階段 6/15/2026
  • 初選第二階段 6/22/2026
  • 校際選修 8/24/2026
  • 初選第三階段 8/31/2026
  • 開學後加退選 9/7/2026
  • 逾期加退選 9/21/2026
選課資源

大型語言模型與資訊安全系統

Applying Large Language Models in Cybersecurity Systems

學期
114-2
學分
3 學分
當期課號
578103
永久課號
AAAI30014
開課單位
AI聯盟學分學程(研究所)
授課教師
林俊叡
類別
選修
上課時間表
週一
2
09:00–09:50
大型語言模型與資訊安全系統
3 節連堂
3
10:10–11:00
4
11:10–12:00

* 根據陽明交大上課時間表所列

概述

本課程探討大型語言模型(LLMs)如何重塑資安領域。學生將學習如何運用 AI 於安全任務、資料整理、機器學習與防禦系統開發。透過專題式學習,團隊將設計並測試真實的 AI+資安解決方案,同時思考倫理、治理,以及「保護 AI」與「運用 AI 防禦」的雙重挑戰。 Applying Large Language Models in Cybersecurity Systems introduces students to the rapidly evolving intersection of artificial intelligence and cyber defense. The course explores how large language models (LLMs) are transforming cybersecurity practice, from automated threat detection to intelligent defense solutions, while also addressing the unique security challenges AI itself introduces. Students will begin by examining the question “Can AI defend with us?”—a guiding theme that frames the role of AI as both an ally and a potential risk in digital security. The course then surveys the evolution of AI with a cybersecurity focus, real-world case studies, and the key terminology that shapes the field. Practical skills are emphasized through modules on effective prompting, data curation for threat intelligence, and applying machine learning techniques to security problems. Students will gain hands-on experience in designing, developing, and evaluating AI-powered cyber defense systems, while also considering governance, ethics, and security implications. A distinctive feature of the course is its Project-Based Learning (PBL) track, where students work in teams to translate theoretical knowledge into practical solutions. Through progressive milestones—requirements, design, proof of concept, and final solution—students will learn how to build and evaluate AI-driven security applications that can operate in real-world environments. By the end of the course, students will be equipped not only with technical competencies in AI and cybersecurity integration, but also with the critical perspective required to navigate ethical, organizational and security governance challenges.

評分方式

● Weekly assignments are graded on a scale of 1–5 points (0 if not submitted). ● The total score is calculated as 20 base points + the sum of all assignment points, with a maximum of 100 points.

週次計畫
週次主題
第 1 週Can AI cyber defend with us?
第 2 週AI Evolution, a cybersecurity focus
第 3 週True AI+ Cybersecurity Stories
第 4 週AI & Cybersecurity Lingo
第 5 週Prompting AI for Cybersecurity
第 6 週Data Curation for Cybersecurity
第 7 週Machine Learning for Cybersecurity
第 8 週Developing AI-powered Cyber Defense
第 9 週Governing Ethics and Security
第 10 週True AI+ Cybersecurity Stories
第 11 週AI for Cybersecurity
第 12 週Cybersecurity for AI
第 13 週PBL: AI+ Security Requirements
第 14 週PBL: AI+ Security Design
第 15 週PBL: AI+ Security POC
第 16 週PBL: AI+ Security Solution
教科書

指定書目 Think Artificial Intelligence: A Student’s Guide to AI’s Building Blocks, by Jerry Cuomo 參考書目 Practical AI for Cybersecurity, by Ravi Das ChatGPT for Cybersecurity Cookbook: Learn Practical Generative AI Recipes to Supercharge Your Cybersecurity Skills, by Clint Bodungen