This unit explores the essential knowledge and skills of data science and big data analytics, in particular, their applications into cyber security. Content includes: in-depth study of large-scale data management, processing, mining, curation, and analysis; big data technologies, e.g., batch processing and stream processing, as well as tools, e.g., Hadoop and MapReduce; challenges of data security, e.g., data provenance, privacy, and secure storage; topics on security analytics, e.g., analytics model, threat detection analytics, botnet identification, and events analytics.

Unit details

Study level:
Credit points:
Unit code:


NIT2102 - Cyber Security Essentials or

NIT2202 - Big Data

Learning Outcomes

On successful completion of this unit, students will be able to:
  1. Apply appropriate data analytics methodologies and tools to improve the business intelligence;  
  2. Program and develop applications to implement data analytics techniques;  
  3. Implement a framework to achieve data security in Internet;  
  4. Design analytics solutions for a variety of cyber attacks.  


Assessment type Description Grade
Laboratory Work Practical Lab Work (2 hours) 25%
Assignment Individual Assignment (solving practical problems) 35%
Examination Final Written Examination (3 hours) 40%

Required reading

Lecturer may supply additional reading material.

Computer Security Fundamentals 3rd ed.
William Easttom (2016)
Pearson IT Certification

REFERENCE TEXTS: Thomas Erl, Wajid Khattak, and Paul Buhler (2016) Big Data Fundamentals: Concepts, Drivers & Techniques 1st ed., Prentice Hall

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