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DATA SECURITY ANALYSIS USING MACHINE LEARNING AND VISUALIZATION ON CYBER SECURITY
  • Sandeep Kumar,
  • Dilip Kumar Shaw
Sandeep Kumar
National Institute of Technology Jamshedpur

Corresponding Author:[email protected]

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Dilip Kumar Shaw
National Institute of Technology Jamshedpur
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Abstract

In the field of Cyber Security (CS), detecting cyber abnormalities along with threats is an increasing concern these days. In daily living, CS plays a significant part to safeguard the individuals who utilize the internet by means of various electronic tools. The famous Machine Learning (ML) classification methodologies like Logistic regression, K-nearest neighbors, Naïve Bayes (NB), stochastic gradient descent, Decision Tree (DT), extreme Gradient Boosting, Adaptive Boosting, and Support Vector Machine (SVM) are used for constructing the data security method. Owing to the rise in the number of hackings, CS is gaining more recognition. To handle this issue, the visualization of data is employed to create awareness. For tracking every user who has used the server, log files are utilized. To acquire a good knowledge of the security log files, charts along with graphs are used. Thus, the following are discussed here: CS and its challenges, data security analysis on CS utilizing ML methodologies, CS models are compared, visualizations on CS, along with challenges faced for efficient data visualization in CS. Malware detection’s accuracy performance utilizing ML methodologies is examined. Regarding recall, accuracy, precision, along with F-score, several ML-centric structures are effectively compared and examined.