Cybersecurity Data Analysis for INSS


GOAL

RESULT

DURATION

The primary objective for this project was to perform a detailed statistical analysis of metadata provided by INSS, aimed at extracting meaningful insights. The goal was to use these insights, supported by comprehensive plots and visualizations, to enhance the strategic decision-making process in cybersecurity initiatives and threat mitigation strategies.





































The analysis provided key insights that were included in an INSS-published paper, enhancing cybersecurity strategies. The visualizations helped clarify data trends, improving responses to cyber threats.





























This intensive project spanned 2 months, involving meticulous data gathering and analysis phases to ensure comprehensive coverage and accuracy of findings.











WHAT CHARACTERISTICS ARE SPECIFIC TO CYBERSECURITY THREATS?


Key characteristics identified included:


  • IP addresses and geographic locations of servers
  • Types of malware used in previous attacks
  • Communication patterns between specific attacking groups
  • Historical data on cyberattack tactics


Using these data points, the model could predict potential cybersecurity breaches more accurately.



WHAT IS THE STRATEGIC SECURITY VALUE FOR EACH PREDICTION?


Each prediction helped in quantifying the potential impact of a breach, thereby aiding in the allocation of resources towards the most threatening predictions and enhancing proactive defensive strategies.


HOW CAN WE PREDICT POTENTIAL CYBERSECURITY BREACHES?


A combination of Large Language Models and sophisticated tools was employed to analyze complex data sets. The predictive model then ranked potential threats based on the likelihood and potential impact, helping strategists focus on high-risk areas with precision.