精东传媒app

UniSQ Logo
The current and official versions of the course specifications are available on the web at .
Please consult the web for updates that may occur during the year.

CIS5206 Data Mining for Business Analytics and Cyber Security

Units : 1
Faculty or Section : Faculty of Business, Education, Law and Arts
School or Department : School of Business
Grading basis : Graded
Course fee schedule : /current-students/administration/fees/fee-schedules

Overview

Detecting and preventing cyber-attacks becomes increasingly important in order to protect businesses from cyber terrorism threats. Data mining techniques can be effective in tackling cyber security challenges. This course provides critical knowledge required to understand the application of data mining to cyber threats in order to protect businesses from any unforeseen cyber-attacks.

This course provides an overview of the different types of cyber-attacks, the business systems that are most at risk, and the strengths and challenges of data mining approach to cybersecurity. The course will cover data mining algorithms including prediction, classification, clustering mechanisms, and association rules, which have all been used to discover and generalize attack patterns so as to develop powerful business solutions for dealing with the threats. Students will also learn various applications of data mining that can be utilised in the real-time detection of threats. The course also provides an opportunity for hands-on experimentation with applying data mining to real-life security problems in the practical workshop with real-world data.

Course offers

精东传媒app period Mode Campus
Semester 1, 2022 On-campus Springfield
Semester 1, 2022 On-campus Toowoomba
Semester 1, 2022 Online
Semester 2, 2022 On-campus Springfield
Semester 2, 2022 On-campus Toowoomba
Semester 2, 2022 Online
Date printed 10 February 2023