Results 181 to 190 of about 20,046 (244)

Adversarial Samples on Android Malware Detection Systems for IoT Systems. [PDF]

Sensors (Basel), 2019
Liu X, Du X, Zhang X, Zhu Q, Wang H, Guizani M.   +5 more
europepmc   +1 more source

Enhancing Android Malware Detection with XGBoost and Convolutional Neural Networks

Atif Raza Zaidi, Tahir Abbas, Ali Daud, Omar Alghushairy, Hussain Dawood, Nadeem Sarwar   +5 more
openalex   +1 more source

Comparing Conformer, Genetic Artificial Intelligence Conformer, and Active Learning Conformer Approaches for Encrypted Android Malware Traffic Detection

Md. Shakib
openalex   +1 more source

Detecting and classifying method based on similarity matching of Android malware behavior with profile. [PDF]

Springerplus, 2016
Jang JW, Yun J, Mohaisen A, Woo J, Kim HK.   +4 more
europepmc   +1 more source

Detección de malware en android utilizando aprendizaje automático.

, 2018
Alejandro Pérez Fals
openalex   +1 more source

Reverse Engineering for Static Analysis of Android Malware in Instant Messaging Apps

I Gede Adnyana Adnyana, Putu Gede Surya Cipta Nugraha, Bagus Rahmat Adin Nugroho   +2 more
openalex   +2 more sources

Detection of android malware with deep learning method using convolutional neural network model

Reza Maulana, Deris Stiawan, Rahmat Budiarto   +2 more
openalex   +2 more sources

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

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

A distributed framework for zero-day malware detection using federated ensemble models. [PDF]

PLoS One
Ishfaq H, Shah JH, Saleem R, Afzal M.
europepmc   +1 more source