Feb 28, 2022 · We propose a novel malware detection model in this paper. This model combines a grey-scale image representation of malware with an autoencoder network in a ...
Mar 10, 2022 · This model combines a grey-scale image representation of malware with an autoencoder network in a deep learning model, analyses the feasibility ...
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Abstract—Research in the field of malware detection is currently leaning toward methods based on artificial intelligence algorithms due to the increasing ...
... Autoencoder was trained using one malware family data at the time, achieving better image reconstruction of malware image. The resulting system performed ...
Duration: 16:13
Posted: Dec 24, 2023
Posted: Dec 24, 2023
In this paper, we propose a deep learning approach for Android malware detection. The proposed approach investigates five different feature sets and applies ...
classification and detection. Malware detection methods leveraging deep learning models predominantly employ neural networks, recurrent neural networks ...
A malware detection system that transforms malware files into image representations and classifies the image representation with CNN is designed and results ...
In a deep learning model, this model combines a grey-scale picture representation of malware with an autoencoder network, examines the viability of the grey- ...
We propose DroidEncoder, a novel autoencoder-based model to classify Android malware applications. On the grounds of this, an image-based Android app dataset ...