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UNDERGRADUATE COURSES

Data Mining for Cybersecurity(網(wǎng)絡空間安全數(shù)據(jù)挖掘技術)

DATE :Jan 20, 2020                     source :

Course code314067030

Course titleData Mining for Cybersecurity

Credit3                  

Hours48

Assessment: Non Test Courses

Prerequisite courses: Object-oriented Programming, Computer Networking, Operating System Principles

Basic Orientation: Students in Cybersecurity

Books:

Data Mining Technology in Network Security, Li Tao, etc., Tsinghua University Press, 2017.8

Reference

(1). Data Driven Security, Jay Jacobs, Bob Rudis, Machinery Industry Press, 2015.9

(2). Machine Learning, Zhou Zhihua, Tsinghua University Press, 2016.1

(3). .Python Natural Language Processing, Steven et al., People's Posts and Telecommunications Press, 2014.6

(4). Introduction to Machine Learning for Web Security, Liu Kun, Machinery Industry Press, 2017.8

(5). https://study.163.com/course/introduction/1004570029.htm

(6). Stanford (Data Mining for Cyber Security) https://web.stanford.edu/class/cs259d/

(7). Indiana University Bloomington (Data-driven Security and Privacy) https://www.xiaojingliao.com/780dsp.html


Course objectives and contents

The sharp rise in new cyber-attack rates has made data mining-based technologies become a key point in detecting security threats. The cyberspace security data mining technology course covers various applications of data mining in computer and network security. According to recent security research papers, it includes common machine learning threat detection models, and the topics cover the elements of data processing technology (such as natural language processing, Machine learning), the application of data processing technologies in various security and privacy issues (SQL injection attacks, XSS attacks, Webshell, phishing URLs, DGA domain names, malware detection methods, etc.), and introduce these solution to solve practical problem.


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