Results 81 to 90 of about 10,938 (187)

Profiling and Visualizing Android Malware Datasets

, 2022
Mobile devices are ubiquitous: nowadays most people own a mobile telephone.Because of this, it is a target of interest for attackers.Researchers in malware analysis put their effort to recognize these types of programs before they are installed on a user device.To do this, they perform experiments to automatically detect malware, for example with ...
openaire   +1 more source

Through the static: Demystifying malware visualization via explainability

Journal of Information Security and Applications
Security researchers grapple with the surge of malicious files, necessitating swift identification and classification of malware strains for effective protection. Visual classifiers and in particular Convolutional Neural Networks (CNNs) have emerged as vital tools for this task.
Brosolo, Matteo, P., Vinod, Conti, Mauro
openaire   +2 more sources

Deep visualization classification method for malicious code based on Ngram-TFIDF

Tongxin xuebao
With the continuous increase in the scale and variety of malware, traditional malware analysis methods, which relied on manual feature extraction, become time-consuming and error-prone, rendering them unsuitable.
WANG Jinwei, CHEN Zhengjia, XIE Xue, LUO Xiangyang, MA Bin   +4 more
doaj   +2 more sources

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

DaViz: Visualization for Android Malware Datasets

, 2022
With millions of Android malware samples available, researchers have a large amount of data to perform malware detection and classification, specially with the help of machine learning. Thus far, visualization tools focus on single samples or one-to-many comparison, but not a many-to-many approach.
Concepción Miranda, Tomás, Lalande, Jean-François, Viet Triem Tong, Valérie, Wilke, Pierre   +3 more
openaire   +1 more source

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

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

Cyber security situational awareness [PDF]

, 2016
Tianfield, Huaglory
core   +1 more source

On Visual Hallmarks of Robustness to Adversarial Malware

, 2018
A central challenge of adversarial learning is to interpret the resulting hardened model. In this contribution, we ask how robust generalization can be visually discerned and whether a concise view of the interactions between a hardened decision map and input samples is possible.
Huang, Alex, Al-Dujaili, Abdullah, Hemberg, Erik, O'Reilly, Una-May   +3 more
openaire   +2 more sources

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