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Malware Detection Using Deep Learning and Correlation-Based Feature Selection

Malware is one of the most frequent cyberattacks, with its prevalence growing daily across the network. Malware traffic is always asymmetrical compared to benign traffic, which is always symmetrical. Fortunately, there are many artificial intelligence techniques that can be used to detect malware an...

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書誌詳細
主要な著者:	Alomari E.S., Nuiaa R.R., Alyasseri Z.A.A., Mohammed H.J., Sani N.S., Esa M.I., Musawi B.A.
その他の著者:	58668473000
フォーマット:	論文
出版事項:	MDPI 2024
主題:	deep learning dense model feature selection LSTM malware detection
タグ:	タグ追加タグなし, このレコードへの初めてのタグを付けませんか!

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