Group01 Report
LINK TO PROJECT GROUPS:
Please Click Here -> [1]
Cybersecurity
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Contents
Introduction
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Objective and Motivations
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Previous Works
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Dataset and Data Preparation
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Design Framework and Visualization Methodologies
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Insights and Implications
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Limitation and Future Work
The app in its current iteration is not designed for real-time monitoring. Future work would include adapting the code to ingest real-time data and create a loop to refresh the analysis periodically. The time taken to refresh the analysis would be shorter than the interval in which network traffic is analysed for suspicious activity. The app could be deployed within Big Data Architecture that use Apache Spark for analysis, which is a common solution, as the Spark engine comes with APIs for R. In fact, with enough data points, the dashboard could even be expanded to include a predictive module that anticipates where and when the next cyber-attack will take place. |
Conclusion
This project attempts to tackle the complexity of cybersecurity and visualise suspicious attacks that are highly likely to be actual attacks in a meaningful and intuitive manner. That is not an easy task given that cyber-attacks can take place at any time, from anywhere, at any intensity (e.g. number of connections) and in many different forms. Hence tools to aid cybersecurity experts in detecting and defending against cyber-attacks need to continually be refined and upgraded. This project is a first step in that direction. |
References
[1] Shneiderman, B. (2005) “The eyes have it: A task by data type taxonomy for information visualization” IEEE Conference on Visual Languages (VL96), pp. 336-343 |
