Results 151 to 160 of about 2,904 (224)

Deep learning-based improved transformer model on android malware detection and classification in internet of vehicles. [PDF]

Sci Rep
Almakayeel N.
europepmc   +1 more source

PermQRDroid: Android malware detection with novel attention layered mini-ResNet architecture over effective permission information image. [PDF]

PeerJ Comput Sci
Kılıç K, Doğru İA, Toklu S.
europepmc   +1 more source

PermDroid a framework developed using proposed feature selection approach and machine learning techniques for Android malware detection. [PDF]

Sci Rep
Mahindru A, Arora H, Kumar A, Gupta SK, Mahajan S, Kadry S, Kim J.   +6 more
europepmc   +1 more source

OmBNNet: a resource-efficient FPGA-based obfuscated malware detection method using binarized neural network. [PDF]

Sci Rep
Das K, Borah BB, Bhattacharyya DK, Kalita J.   +3 more
europepmc   +1 more source

Efficient feature ranked hybrid framework for android Iot malware detection. [PDF]

Sci Rep
Saeed NH, Hamza AA, Sobh MA, Bahaa-Eldin AM.   +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

Improving malware detection performance using hybrid deep representation learning with heuristic search algorithms. [PDF]

Sci Rep
Anuradha A, Chouhan AS, Srinivas Rao S.
europepmc   +1 more source

DEFEAT: Android device behavior-based datasets for multi-stage APT. [PDF]

Data Brief
Jabar T, Al-Kadhimi AA, Singh MM.
europepmc   +1 more source

MH-1M: A 1.34 Million-Sample Multi-Feature Android Malware Dataset with Rich Metadata. [PDF]

Sci Data
Bragança H, Kreutz D, Rocha V, Assolin J, Feitosa E.   +4 more
europepmc   +1 more source

FL-MalDrift: a federated learning framework for malware detection under local concept drift. [PDF]

Sci Rep
Patel A, Tomar DS, Pateriya RK, Haripriya R.   +3 more
europepmc   +1 more source