MN623 - Cyber Security and Analytics

Credit Points: 20 credit points

Workload: 60 hours

Prerequisite: MN502 Overview of Network Security

Co-requisite: N/A

Aims & Objectives

This is a core unit out of a total of 12 units in the Master of Networking (MNet). This unit addresses the MNet course learning outcomes and complements other courses in a related field by developing students’ specialised knowledge of cyber security solutions based on intelligent data analytic tools and technologies. For further course information refer to: This unit is part of the AQF level 9 (MNet) course.

This unit evaluates and applies contemporary intelligent cyber security solutions for enterprise use. Students will be able to provide advanced security solutions to the business enterprises with in-depth knowledge of cyber threats and its corresponding security protocols. 
The students will exercise their skills and knowledge of data analytics in selecting and deploying advanced and intelligent cybersecurity systems for enterprise security.

This unit will cover the following topics:

  • Advanced threats and attacks on enterprise systems (cracking, spoofing, hijacking, and resource attacks)
  • Risk management and standards
  • Security technologies (Access control, Firewalls, VPNs, and Intrusion Detection System)
  • Data classification and management for risk assessment
  • Decision support system for security control
  • Intelligent security management systems

Learning Outcomes

4.1 Course Learning Outcomes
The Course learning outcomes applicable to this unit are listed on the Melbourne Institute of Technology’s website: 

4.2 Unit Learning Outcomes
At the completion of this unit students should be able to:

  1. Analyse cyber security vulnerabilities using ethical hacking methodologies
  2. Implement and evaluate security testing tools in a realistic computing environment
  3. Evaluate intelligent security solutions based on data analytics 
  4. Analyse and interpret results from descriptive and predictive data analysis
  5. Propose cyber security solutions for business case studies

Weekly Topics

This unit will cover the content below:

Week Topics
1 Introduction to cybersecurity for enterprise data analytics, & standards
2 Threats and attacks on Enterprise: advanced encryption and password cracking
3 Threats and attacks on Enterprise: advanced spoofing & Session Hijacking
4 Attacking on network devices & Anomaly Detection for enterprise security & Advanced malware analysis
5 Assess risks, and manage strategy and tactics
6 Information management Securing networks and electronic communications. Firewall, Advanced Intrusion Detection Systems
7 Data Mining Techniques for IDS
8 Application of Data Analytics in Enterprise Security
9 Decision support system with data analytics
10 Security control system with data analytics
11 Intelligent and self-evolving security system
12 Review and future trends in intelligent security systems


Assessment Task Due Date Release Date A B Learning Outcomes Assessed
Formative Assignment 1 Week 3 (10/4/2022) Week 1 5%   a
In-class test (On Campus, Face to Face) Week 7 (2/5/2022)     10% a-b
Assignment 2 Group Week 11 (31/5/2022) Week 6 25%   c-e
Class participation & contribution Week 2-11(6/6/2022) Week 2-11 10%   a-e
Final Examination (3 hours)       50% a-e
TOTALS     40% 60%  

Task Type: Type A: unsupervised, Type B: supervised.

Class Participation and Contribution
This unit has class participation and student contribution as an assessment. The assessment task and marking rubric will follow the Guidelines on Assessing Class Participation ( Further details will be provided in the assessment specification on the type of assessment tasks and the marking rubrics.

Textbook and Reference Materials

  • W.Stallings. Effective Cybersecurity: A Guide to Using Best Practices and Standards. First edition, Publisher: Addison-Wesley Professional. Release 2019
  • C. Chio,‎ D. Freeman, Machine Learning and Security: Protecting Systems with Data and Algorithms, O’Reilly Media Inc., 1st Ed., 2018


  • M.T. Simpson, K. Backman, J. Corley, Hands-On Ethical Hacking and Network Defense, 3rd Edition, 2017 
  • E. Ozkaya, Y. Diogenes, Cybersecurity - Attack and Defense Strategies, ISBN: 9781788475297, Packt Publishing, January 2018
  • W. Easttom Penetration Testing Fundamentals: A Hands-On Guide to Reliable Security Audits, First edition by Published by Pearson IT Certification, 2018 
  • M. E. Whitman, H. J. Mattord, Principles of Information Security, Cengage, 6th Ed., 2018
  • D. Sutton, Cyber Security: A Practitioner’s Guide, BSC Learning and Development Ltd, UK, 2017
  • S. Ali, T. A. Balushi, Z. Nadir, O. K. Hussain, Cyber Security for Cyber Physical Systems, Springers, Australia, 2018


Adopted Reference Style: IEEE


Graduate Attributes

MIT is committed to ensure the course is current, practical and relevant so that graduates are “work ready” and equipped for life-long learning. In order to accomplish this, the MIT Graduate Attributes identify the required knowledge, skills and attributes that prepare students for the industry.
The level to which Graduate Attributes covered in this unit are as follows:

Ability to communicate Independent and Lifelong Learning Ethics Analytical and Problem Solving Cultural and Global Awareness Team work Specialist knowledge of a field of study


Levels of attainment Extent covered
The attribute is covered by theory and practice, and addressed by assessed activities in which the students always play an active role, e.g. workshops, lab submissions, assignments, demonstrations, tests, examinations.
The attribute is covered by theory or practice, and addressed by assessed activities in which the students mostly play an active role, e.g. discussions, reading, intepreting documents, tests, examinations.
The attribute is discussed in theory or practice; it is addressed by assessed activities in which the students may play an active role, e.g. lectures and discussions, reading, interpretation, workshops, presentations.
The attribute is presented as a side issue in theory or practice; it is not specifically assessed, but it is addressed by activities such as lectures or tutorials.
The attribute is not considered, there is no theory or practice or activities associated with this attribute.