Original article was published by Richmond Alake on Artificial Intelligence on Medium
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Recommended read for Data Science students and ML practitioners with interest CyberSecurity.
Victor Basu documents a research experiment that explores the utilisation of Machine Learning and Deep Learning techniques to classify DDoS (distributed denial-of-service) attacks. A standard method of network infiltration used by hackers.
Victor’s article applies ML/Data Science techniques to a CyberSecurity use case, an area of computing that has risen in popularity in correlation to the adoption of A.I. based applications.
There’s a wealth of knowledge to be obtained from this article. There’s an inclusion of typical data science project processes that one might encounter such as data gathering, exploratory data analysis or model implementation.
Victor also includes essential topics such as data memory management and training visualisation.
Machine Learning practitioners will appreciate the versatile approach to detecting DDoS attacks that Victor has implemented. The experiment covers both supervised and unsupervised ML approached to classification.
Relevant code snippets and visualisation materials are provided in the article.