Introduction to Industrial Chemistry
| Numbering Code | U-ENG27 17405 LJ60 | Year/Term | 2022 ・ First semester |
|---|---|---|---|
| Number of Credits | 2 | Course Type | Lecture |
| Target Year | Target Student | ||
| Language | Japanese | Day/Period | Wed.1 |
| Instructor name |
ABE TAKESHI (Graduate School of Engineering Professor) SATOU TOORU (Fukui Institute for Fundamental Chemistry Professor) NAKAMURA YOU (Graduate School of Engineering Professor) MIURA KIYOTAKA (Graduate School of Engineering Professor) ABE RYUU (Graduate School of Engineering Professor) MATSUBARA SEIJIROU (Graduate School of Engineering Professor) NAKAO YOSHIAKI (Graduate School of Engineering Professor) KONDOU TERUYUKI (Graduate School of Engineering Professor) OGOSHI TOMOKI (Graduate School of Engineering Professor) SUGINOME MICHINORI (Graduate School of Engineering Professor) FUKAZAWA AIKO (Institute for Integrated Cell-Material Sciences Professor) OTSUKA KOJI (Graduate School of Engineering Professor) SUGIYASU KAZUNORI (Graduate School of Engineering Professor) MATSUMIYA YUMI (Institute for Chemical Research Associate Professor) ATOMI HARUYUKI (Graduate School of Engineering Professor) NUMATA KEIJI (Graduate School of Engineering Professor) KAWASE MOTOAKI (Graduate School of Engineering Professor) SOTOWA KENICHIRO (Graduate School of Engineering Professor) |
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| Schedule and Contents |
Guidance,2times,Guidance on how this class is operated, and how to use computing facility for this class. Basic knowledge on the role of IDS in network security and how machine learning can help the intrusion detection. Intrusion Detection by Signature-Based IDS,5times,Learn the mechanism of intrusion detection by signature-based IDS by studying open source signature-based IDS and attacks, such as correspondence between alarms issued from IDS and communications, and adding signatures to detect attacks. Intrusion Detection by Machine Learning,7times,Learn the method of classifying normal and malicious traffic by machine learning algorithms and public dataset for benchmarking intrusion detection performance. Presentation,1time,Based on the exercise, students presents their methods of intrusion detection using machine learning, and discuss it with other students and instructors. |
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| Course Requirements | None | ||
| Related URL | |||
