High Accuracy Detection of Mobile Malware Using Machine Learning

As increasingly sophisticated and evasive malware attacks continue to emerge, more effective detection solutions to tackle the problem are being sought through the application of advanced machine learning techniques. This reprint presents several advances in the field including: a new method of gene...

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Format:	Online
Sprache:	Englisch
Veröffentlicht:	MDPI - Multidisciplinary Digital Publishing Institute 2023
Schlagworte:	malware analysis and detection applied machine learning mobile security neural network ensemble classification botnet detection deep learning Android botnets convolutional neural networks dense neural networks recurrent neural networks long short-term memory gated recurrent unit CNN-LSTM CNN-GRU Android security malware detection code vulnerability machine learning malware static analysis dynamic analysis hybrid analysis security Monte-Carlo simulation reinforcement learning adversarial sample convolutional neural network Histogram of Oriented Gradients image processing android botnets digital forensic optimization multilayer perceptron salp swarm algorithm connection weights business email compromise (BEC) email phishing phishing detection machine learning (ML) systematic literature review steganography steganalysis polyglots neural networks n/a thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries
Online-Zugang:	ONIX_20230511_9783036571751_12
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ONIX_20230511_9783036571751_12

High Accuracy Detection of Mobile Malware Using Machine Learning

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