Analysis of Bayesian Classification based Approaches for Android Malware Detection

20 August 2016

Papers citing "Analysis of Bayesian Classification based Approaches for Android Malware Detection"

13 / 13 papers shown

Title
Experience Report on the Challenges and Opportunities in Securing Smartphones Against Zero-Click Attacks Narmeen Shafqat Cem Topcuoglu E. Kirda Aanjhan Ranganathan 12 1 0 06 Nov 2022
DroidRL: Reinforcement Learning Driven Feature Selection for Android Malware Detection Y. Wu Meijin Li Junfeng Wang Zhiyang Fang Qi Zeng Tao Yang Luyu Cheng 49 49 0 05 Mar 2022
Using Deep Neural Network for Android Malware Detection Abdelmonim Naway Yuancheng Li 59 14 0 16 Jan 2019
Android Malware Detection Using Autoencoder Abdelmonim Naway Yuancheng Li 31 17 0 14 Jan 2019
Android Malware Characterization using Metadata and Machine Learning Techniques I. Martín José Alberto Hernández Alfonso Muñoz Antonio Guzmán 16 29 0 12 Dec 2017
Malware Detection Approach for Android systems Using System Call Logs Sanya Chaba Rahul Kumar Rohan Pant M. Dave 20 29 0 26 Sep 2017
N-gram Opcode Analysis for Android Malware Detection Boojoong Kang S. Yerima S. Sezer K. Mclaughlin 69 49 0 05 Dec 2016
High Accuracy Android Malware Detection Using Ensemble Learning S. Yerima S. Sezer Igor Muttik FedML 79 165 0 02 Aug 2016
Android Malware Detection Using Parallel Machine Learning Classifiers S. Yerima S. Sezer Igor Muttik 46 137 0 27 Jul 2016
DynaLog: An automated dynamic analysis framework for characterizing Android applications Mohammed K. Alzaylaee S. Yerima S. Sezer AAML 57 56 0 27 Jul 2016
N-opcode Analysis for Android Malware Classification and Categorization Boojoong Kang S. Yerima K. Mclaughlin S. Sezer 40 95 0 27 Jul 2016
Android Malware Detection: an Eigenspace Analysis Approach S. Yerima S. Sezer Igor Muttik 79 26 0 27 Jul 2016
A machine learning approach to anomaly-based detection on Android platforms J. Abah Waziri O.V Abdullahi M.B Arthur U.M Adewale O.S 27 20 0 13 Dec 2015