Course code：314067030
Course title：Data Mining for Cybersecurity
Credit：3
Hours：48
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.
