Visualizing and Predicting the type of Malware in Security Dataset with Machine Learning using Python libraries and Tableau
Rahul Bajaj, Srishti Kohli
security, malware, decision tree, random-forest, logistic regression
In this paper, the different varieties of malware have been introduced and explained. Using Tableau we have implemented a few visualisation techniques on a malware dataset to visualise the prime characteristics and attributes of the various kinds of malware. Furthermore, we have used python libraries for classification of malware from the data provided in the malware dataset, using machine learning algorithms (primarily Decision Trees and its variations) in jupyter notebook, to obtain a high level of accuracy.
Article Details
Unique Paper ID: 148055

Publication Volume & Issue: Volume 5, Issue 12

Page(s): 632 - 638
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Last Date 25 February 2020

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