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- W4301354582 abstract "This paper presents the machine learning algorithm to detect whether an executable binary is benign or ransomware. The ransomware cybercriminals have targeted our infrastructure, businesses, and everywhere which has directly affected our national security and daily life. Tackling the ransomware threats more effectively is a big challenge. We applied a machine-learning model to classify and identify the security level for a given suspected malware for ransomware detection and prevention. We use the feature selection data preprocessing to improve the prediction accuracy of the model." @default.
- W4301354582 created "2022-10-05" @default.
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- W4301354582 date "2022-06-01" @default.
- W4301354582 modified "2023-09-27" @default.
- W4301354582 title "Improving the Prediction Accuracy with Feature Selection for Ransomware Detection" @default.
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- W4301354582 doi "https://doi.org/10.1109/compsac54236.2022.00072" @default.
- W4301354582 hasPublicationYear "2022" @default.
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