A hierarchical deep learning framework with doubly regularized loss for robust malware detection and family categorization. [PDF]
Sci RepAbed Alsaedi S +6 more
europepmc +1 more source
En la actualidad, los emprendedores de la ciudad de Ambato se encuentran en una creciente dependencia de los dispositivos móviles para llevar a cabo sus operaciones comerciales.
Chacha Chadan, Édgar Fabricio
core +1 more source
Systematic Evaluation of Machine Learning and Deep Learning Models for IoT Malware Detection Across Ransomware, Rootkit, Spyware, Trojan, Botnet, Worm, Virus, and Keylogger. [PDF]
Sensors (Basel)Maghanaki M +3 more
europepmc +1 more source
BERT-spaCy hybrid NLP and blockchain-enhanced adaptive CTI for IOC extraction and threat prediction. [PDF]
Sci RepMishra S, Alfahidah RA, Alharbi F.
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MH-1M: A 1.34 Million-Sample Multi-Feature Android Malware Dataset with Rich Metadata. [PDF]
Sci DataBragança H +4 more
europepmc +1 more source
AI-driven cybersecurity for industrial internet of things: architectures, challenges, datasets, and future research directions. [PDF]
Front Big DataSinghal S, Kumar KA.
europepmc +1 more source
Efficient feature ranked hybrid framework for android Iot malware detection. [PDF]
Sci RepSaeed NH +3 more
europepmc +1 more source
A distributed framework for zero-day malware detection using federated ensemble models. [PDF]
PLoS OneIshfaq H, Shah JH, Saleem R, Afzal M.
europepmc +1 more source
MaSS-Droid: Android Malware Detection Framework Using Multi-Layer Feature Screening and Stacking Integration. [PDF]
Entropy (Basel)Zhang Z, Han Q, Shi Z.
europepmc +1 more source
GCSA-ResNet: a deep neural network architecture for Malware detection. [PDF]
Sci RepFan Y +5 more
europepmc +1 more source