Results 111 to 120 of about 5,547 (215)

Fast automated unpacking and classification of malware

, 2010
"Malware is a pervasive problem in distributed computer and network systems. Identification of malware variants provides great benefit in early detection.
Silvio Cesare (9786254)
core   +2 more sources

An ensemble approach for imbalanced multiclass malware classification using 1D-CNN. [PDF]

PeerJ Comput Sci, 2023
Panda B, Bisoyi SS, Panigrahy S.
europepmc   +1 more source

FedDroidMeter: A Privacy Risk Evaluator for FL-Based Android Malware Classification Systems. [PDF]

Entropy (Basel), 2023
Jiang C, Xia C, Liu Z, Wang T.
europepmc   +1 more source

Wavelet-Based and MAML-Driven Framework for Enhanced Few-Shot Malware Classification

Applied Sciences
Traditional malware classification approaches primarily address fixed sets of well-studied malware types and therefore struggle to accommodate the continual emergence of novel or previously unseen malware strains.
Abdullah Almuqrin, Ibrahim Mutambik, Majed Abusharhah   +2 more
doaj   +1 more source

MalFuzz: Coverage-guided fuzzing on deep learning-based malware classification model. [PDF]

PLoS One, 2022
Liu Y, Yang P, Jia P, He Z, Luo H.
europepmc   +1 more source

Malware Generation and Classification using PixelCNN

Malware poses a serious threat to both data privacy and system security. With the wide variety of malware families and the surge in cyber-attacks, the accurate classification of malware is crucial for building effective detection and prevention systems ...
Karumudi, Mounika Krishna Teja
core   +1 more source

TRConv: Multi-Platform Malware Classification via Target Regulated Convolutions

IEEE Access
Malware is an important threat to digital workflow. Traditional malware modeling approaches focused on using hand-crafted features while recent approaches proved the necessity of using learning based methodologies.
Alper Egitmen, Ali Gokhan Yavuz, Sirma Yavuz   +2 more
doaj   +1 more source

AndroMalPack: enhancing the ML-based malware classification by detection and removal of repacked apps for Android systems. [PDF]

Sci Rep, 2022
Rafiq H, Aslam N, Aleem M, Issac B, Randhawa RH.   +4 more
europepmc   +1 more source

Convolution neural network with batch normalization and inception-residual modules for Android malware classification. [PDF]

Sci Rep, 2022
Liu T, Zhang H, Long H, Shi J, Yao Y.
europepmc   +1 more source

Digital Forensics for Malware Classification: An Approach for Binary Code to Pixel Vector Transition. [PDF]

Comput Intell Neurosci, 2022
Naeem MR, Amin R, Alshamrani SS, Alshehri A.   +3 more
europepmc   +1 more source