Analysis of Android malware detection techniques: A systematic review

MA Ashawa, S Morris - 2019 - dspace.lib.cranfield.ac.uk
The emergence and rapid development in complexity and popularity of Android mobile
phones has created proportionate destructive effects from the world of cyber-attack. Android …

[PDF][PDF] Cybersecurity and Cyber Forensics: Machine Learning Approach Systematic Review

I Goni, JM Gumpy, TU Maigari… - … Science and Information …, 2020 - academia.edu
The proliferation of cloud computing and internet of things has led to the connectivity of
states and nations (developed and develo** countries) worldwide in which global network …

[PDF][PDF] Machine learning approach to mobile forensics framework for cyber crime detection in Nigeria

I Goni, M Mohammad - Journal of Computer Science Research, 2020 - academia.edu
1. Background World is in the state of unique period of history. The current technological
advancement will be among the global transformations remembered by humanity ever …

A Systematic Review of Android Malware Detection Techniques.

FA Alharbi, AM Alghamdi, AS Alghamdi - International Journal of …, 2021 - go.gale.com
Malware detection is a significant key to Android application security. Malwares threat to
Android users is increasing day by day. End users need security because they use mobile …

Machine Learning Algorithms Applied to System Security: A Systematic Review

I Goni - Asian Journal of Applied Science and Technology, 2020 - papers.ssrn.com
Abstract Machine learning are used for numerous functions like image processing, data
mining, prediction analysis, online shop**, cybersecurity, digital forensics, network …

[PDF][PDF] MALWARE VISUALIZATION TECHNIQUE: A SYSTEMATIC REVIEW

A ALAROOD - Journal of Theoretical and Applied Information …, 2019 - jatit.org
Recently, there has been a massive increase in number of malware types which poses a
severe threat to smart devices and to internet security. Thus, different techniques have been …

[PDF][PDF] 一种基于改进的关联规则挖掘算法的 Android 恶意软件检测方法

严喆, 朱保** - 计算机与数字工程, 2018 - jsj.journal.cssc709.net
摘要针对Android **台恶意软件的检测需求的上升和现有的关联规则挖掘算法的效率较低,
不能直接用于恶意软件的检测的问题, 论文在改进的关联规则挖掘算法(Eclat) 的基础之上 …

[NAVEDBA][C] 基于集成分类的恶意应用检测方法

黄伟, 陈昊, 郭雅娟, 姜海涛 - 南京理工大学学报, 2016