Nimra Mushtaq

Academic

Career

Verbatim text

Cyber Threat Intelligence with A Text Mining Approach: An 
Empirical Study of Detecting Phishing, Ransomware, and 
Emerging Threats 
Project Brief:  
Advanced cyber threats exploit business vulnerabilities like socially-engineered phishing 
attempts to compromise user credentials; encryption of businesses through ransomware 
attacks to extort payments, and impersonation of executives through business email 
compromise for fraudulent wire transfers. This empirical research will utilize text mining 
techniques to detect cyber threats and generate intelligence from textual data.  
Research objectives: 
 
Identify relevant text sources related to phishing, ransom ware, business email 
compromise, and other cyber threats facing businesses. 
 
Develop text mining techniques to detect threats and extract indicators from text 
sources. 
 
Evaluate combinations of natural language processing, machine learning, and data 
visualization methods for generating actionable cyber threat intelligence. 
Methodology:  
This methodology can be expected to facilitate an empirical evaluation of different text 
mining techniques for cyber threat detection across various categories of threats faced by 
modern businesses. The findings may advance cyber security capabilities and inform data-
driven threat mitigation strategies. KNIME software is used for generating results. 
 
 
 
Area of Study: 
Cross Cluster 
Supervisor Name: 
Mr. Hammad Majeed 
Group Members:  
Nimra Mushtaq (i20 - 0007)

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