Results 111 to 120 of about 2,905 (223)

Resilient and Scalable Android Malware Fingerprinting and Detection [PDF]

, 2020
Malicious software (Malware) proliferation reaches hundreds of thousands daily. The manual analysis of such a large volume of malware is daunting and time-consuming.
Karbab, ElMouatez Billah
core  

CLASSIFYING ANDROID MALWARE CATEGORIES BASED ON DYNAMIC FEATURES: AN INTEGRATION OF FEATURE REDUCTION AND SELECTION TECHNIQUES

Mağallaẗ Al-kūfaẗ Al-handasiyyaẗ
Android malware has grown steadily into a major internet threat. Despite efforts to identify and categorize malware in seemingly safe Android apps, addressing this issue is still lacking.
abdullah alsraratee, Ahmed Al-Azawei
doaj   +1 more source

Android malware detection using random forest algorithm

Proceedings of the Nigerian Society of Physical Sciences
The proliferation of mobile devices and their dependence on the android OS has made them prime targets for cybercriminals, leading to an escalating threat of malware.
Samson Isaac, Abdullahi Tanimu, Mohammed Shamsuddeen Tukur , Jacob Isaac, Amina Bala Ja'afaru   +4 more
doaj   +1 more source

Intelligent Pattern Recognition Using Equilibrium Optimizer With Deep Learning Model for Android Malware Detection

IEEE Access
Android malware recognition is the procedure of mitigating and identifying malicious software (malware) planned to target Android operating systems (OS) that are extremely utilized in smartphones and tablets.
Mohammed Maray, Mashael Maashi, Haya Mesfer Alshahrani, Sumayh S. Aljameel, Sitelbanat Abdelbagi, Ahmed S. Salama   +5 more
doaj   +1 more source

An Improved Malicious Application Detection in Social Networks (MADSN)

مجلة جامعة الزيتونة, 2021
Android is the most widely used mobile operating system (OS). A large number of third-party Android application (app) markets have emerged. The absence of third-party market regulation has prompted research institutions to propose different malware ...
Nagmden Nasser, Adel Abosdel
doaj  

A pragmatic android malware detection procedure

Computers & Security, 2017
Abstract The academic security research community has studied the Android malware detection problem extensively. Machine learning methods proposed in previous work typically achieve high reported detection performance on fixed datasets. Some of them also report reasonably fast prediction times.
Palumbo, Paolo, Sayfullina, Luiza, Komashinskiy, Dmitriy, Eirola, Emil, Karhunen, Juha   +5 more
openaire   +1 more source

A Lightweight malware detection technique based on hybrid fuzzy simulated annealing clustering in Android apps

Egyptian Informatics Journal
The growing complexity of cyber threats has shifted the focus from merely identifying threats to detecting their origins, resulting in stronger defenses against malware.
Collins Chimeleze, Norziana Jamil, Nazik Alturki, Zuhaira Muhammad Zain   +3 more
doaj   +1 more source

A Combination Method for Android Malware Detection Based on Control Flow Graphs and Machine Learning Algorithms

IEEE Access, 2019
Android malware severely threaten system and user security in terms of privilege escalation, remote control, tariff theft, and privacy leakage. Therefore, it is of great importance and necessity to detect Android malware.
Zhuo Ma, Haoran Ge, Yang Liu, Meng Zhao, Jianfeng Ma   +4 more
doaj   +1 more source

Machine learning methods for Android malware detection [PDF]

, 2015
With the Android mobile device becoming increasingly popular, the Android application market has become a main target of the malware attacks. Therefore, many methods have been used to protect the mobile application users from being attacked.
Xu, Zhengzi
core  

AAGAN: Android Malware Generation System Based on Generative Adversarial Network

Vietnam Journal of Computer Science
With the rapid evolution of mobile malware, especially Android malware, machine learning (ML)-based Android malware detection systems have drawn massive attention. Although ML algorithms have recently led to many vital breakthroughs in malware detection,
Doan Minh Trung, Nghi Hoang Khoa, Phan The Duy, Van-Hau Pham, Nguyen Tan Cam   +4 more
doaj   +1 more source