Jun 18, 2022 · We propose MDCD, a novel dynamic malware detection solution for cloud environments. This method first utilizes a lightweight agent to collect the run-time ...
Jun 18, 2022 · The goal of MDCD is to build a lightweight malware detection system for the virtualized environment. This system can detect whether there are ...
Compared with the existing solutions, our method can detect multiple malicious processes effectively with little deployment effort. AB - With the increasing ...
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To address these issues, we propose MDCHD, a novel malware detection solution for virtualization environments. This method first utilizes the Intel Processor ...
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This paper studies the effectiveness of Recurrent Neural Networks based deep learning techniques for detecting malware in cloud Virtual Machines (VMs), ...
Mar 19, 2023 · This paper proposes a malware detection approach based on convolutional neural network and memory forensics.
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Aug 28, 2024 · I made a website, that uses a neural network to scan binaries for malicious patterns. It currently only identifies windows malware. It's a python script, (code ...
The proposed MFODBN-MDC model primarily undergoes two stages of pre-processing, namely categorical encoding and null value removal. Moreover, the MFODBN-MDC.
In this paper, we present online malware detection based on process level performance metrics, and analyze the effectiveness of different baseline machine ...
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May 20, 2024 · In this paper, we present DeepMetaDroid, a real-time detection approach for Android malware that leverages metadata features.
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