42897 Data Analytics for Cybersecurity Foundations
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Credit points: 2 cp
Result type: Grade and marks
Anti-requisite(s): 41180 Data Analytics in Cyber Security
Description
Data Analytics for Cybersecurity Foundation introduces big data capabilities with threat intelligence to help detect, analyse and alleviate the insider threats, as well as targeted attacks from external bad actors and persistent cyber threats. It includes a number of IT areas, such as data analytics methods for identifying security issues in data; packet analysis for insider threats; Network package and DDoS Attack analysis from external threats; and other intelligent technologies that derive cybersecurity issues from data. Data Analytics for Cybersecurity Foundations introduces students to the significance and language of data analytics for cybersecurity and the most common approach to standard process for data analytics. This subject offers practice in the foundations of data analytics of cybersecurity, including identifying security risks, threats and vulnerabilities to the corporate computers and networks.
Subject learning objectives (SLOs)
Upon successful completion of this subject students should be able to:
| 1. | Apply data analytics to investigate cybersecurity datasets. (D.1) |
|---|---|
Course intended learning outcomes (CILOs)
This subject also contributes specifically to the development of the following Course Intended Learning Outcomes (CILOs):
- Technically Proficient: FEIT graduates apply theoretical, conceptual, software and physical tools and advanced discipline knowledge to research, evaluate and predict future performance of systems characterised by complexity. (D.1)
Teaching and learning strategies
Microcredential presentation includes weekly synchronous one-hour online workshops facilitated by an expert UTS academic(s) supporting self-study and online (LMS) learning activities. Case studies of real-world business illustrate applications of data analytics techniques in cybersecurity. The workshop sessions focus on hands-on experience in cybersecurity and data analytics tools, and the understanding and interpretation of the results. Regular formative quizzes throughout the semester will allow learners to gauge their progress.
Content (topics)
- The introduction of data analytics for cyber security: overview of the significance of cybersecurity in data analysis;
- Fundamental data analytics use Python: introduction to data analysis tools for cybersecurity in Python;
- Packet Analysis for Security: Case study of insider threats by data analysis technology.
- Network package analysis and DDoS Attack: Case study of external attacks by data analysis technology.
Assessment
Assessment task 1: Security Exploration Report
| Intent: | Develop student awareness of the vulnerability of computer systems to cyberattacks in corporate environment |
|---|---|
| Objective(s): | This assessment task addresses the following subject learning objectives (SLOs): 1 This assessment task contributes to the development of the following Course Intended Learning Outcomes (CILOs): D.1 |
| Type: | Report |
| Groupwork: | Individual |
| Weight: | 100% |
| Length: | 2,000 words |
Minimum requirements
In order to pass the microcredential, a learner must achieve an overall mark of 50% or more.