Results 71 to 80 of about 1,517 (174)

WinDroid: A Novel Framework for Windows and Android Malware Family Classification Using Hierarchical Ensemble Support Vector Machines With Multiview Handcrafted and Deep Learning Features

IET Information Security
The rapid growth and diversification of malware variants, driven by advanced code obfuscation, evasion, and antianalysis techniques, present a significant threat to cybersecurity.
K. Sundara Krishnan, S. Syed Suhaila
doaj   +1 more source

ARSNet: A Novel Malware Visualization Detection Method

IEEE Access
Malware detection remains a significant challenge in cybersecurity. To address this, visualization-based methods map binary code into image representations to leverage visual features for rapid identification.
Xinbo Liu, Wei Liu, Peng Nie, Zhuojun Fu
doaj   +1 more source

IMCMK-CNN: A lightweight convolutional neural network with Multi-scale Kernels for Image-based Malware Classification

Alexandria Engineering Journal
Rapid and accurate identification of unknown malware and its variants is the premise and basis for the effective prevention of malicious attacks. However, with the explosive growth of malware variants, the efficiency of manual updating of the sample ...
Dandan Zhang, Yafei Song, Qian Xiang, Yang Wang   +3 more
doaj   +1 more source

Research on lightweight malware classification method based on image domain

Tongxin xuebao
To address the high deployment costs and long prediction times associated with traditional malware classification methods, a lightweight malware visualization classification method was proposed.
SUN Jingzhang, CHENG Yinan, ZOU Binghui, QIAO Tonghua, FU Sizheng, ZHANG Qi, CAO Chunjie   +6 more
doaj  

Advanced behavioral malware detection: a comprehensive MLOps framework with federated learning and real-time drift detection. [PDF]

Front Artif Intell
El-Hajj M, Zeineddine MAJ.
europepmc   +1 more source

RNN-based detection of IoT malware using diverse feature engineering methods. [PDF]

Sci Rep
Abd-Ellah MK, Alsayed NA, Elkomy OM, El-Hady WM.   +3 more
europepmc   +1 more source

A deep learning-based IoT malware detection approach for electric vehicle charging stations. [PDF]

Sci Rep
Xia L, Chen Y, Han L.
europepmc   +1 more source

Malware detection in IoT networks with CNNs and integrated feature engineering. [PDF]

Sci Rep
Abd-Ellah MK, Alsayed NA, Elkomy OM, El-Hady WM.   +3 more
europepmc   +1 more source

Few-shot android malware classification with quantum-enhanced prototypical learning and drift detection. [PDF]

Sci Rep
Tawfik M, Tarazi H, Dalalah A, Bajeszeyadaljunaeidia, Shaban WM, Fathi IS.   +5 more
europepmc   +1 more source

A Survey on Visualization-Based Malware Detection

Journal of Cyber Security, 2022
Ahmad Moawad, Ahmed Ismail Ebada, Aya M. Al-Zoghby   +2 more
openaire   +1 more source