Results 31 to 40 of about 11,847 (201)

Evaluation and classification of obfuscated Android malware through deep learning using ensemble voting mechanism

Scientific Reports, 2023
With the rise in popularity and usage of Android operating systems, malicious applications are targeted by applying innovative ways and techniques.
Sana Aurangzeb, Muhammad Aleem
doaj   +1 more source

A Method for Automatic Android Malware Detection Based on Static Analysis and Deep Learning

IEEE Access, 2022
The computers nowadays are being replaced by the smartphones for the most of the internet users around the world, and Android is getting the most of the smartphone systems’ market.
Mulhem Ibrahim, Bayan Issa, Muhammed Basheer Jasser   +2 more
doaj   +1 more source

KLASIFIKASI MALWARE ANDROID DENGAN MENGGUNAKAN METODE CATBOOST ALGORITMA [PDF]

, 2023
In 2008, Android was introduced as a popular open source project due to its customizability and low hardware requirements. Mid-2021 statistics from GlobalStat Counter shows that Android dominates the mobile operating system market with 72.74%.
IRSYADUDDIN, YUSUF
core  

Android Security: A Survey of Issues, Malware Penetration, and Defenses [PDF]

, 2014
Smartphones have become pervasive due to the availability of office applications, Internet, games, vehicle guidance using location-based services apart from conventional services such as voice calls, SMSes, and multimedia services.
Bharmal, A., Conti, M., Faruki, P., Ganmoor, V., Gaur, M. S., Laxmi, V., Rajarajan, M.   +6 more
core   +1 more source

DroidPortrait: Android Malware Portrait Construction Based on Multidimensional Behavior Analysis

Applied Sciences, 2020
Recently, security incidents such as sensitive data leakage and video/audio hardware control caused by Android malware have raised severe security issues that threaten Android users, so thus behavior analysis and detection research researches of ...
Xin Su, Lijun Xiao, Wenjia Li, Xuchong Liu, Kuan-Ching Li, Wei Liang   +5 more
doaj   +1 more source

ACTS: Extracting Android App Topological Signature through Graphlet Sampling [PDF]

, 2016
Android systems are widely used in mobile & wireless distributed systems. In the near future, Android is believed to dominate the mobile distributed environment.
Al Hasan, Mohammad, Gao, Tianchong, Li, Feng, Peng, Wei, Saha, Tanay Kumar, Sisodia, Devkishen   +5 more
core   +1 more source

Review of Android Malware Detection Based on Deep Learning

IEEE Access, 2020
At present, smartphones running the Android operating system have occupied the leading market share. However, due to the Android operating system's open-source nature, Android malware has increased dramatically.
Zhiqiang Wang, Qian Liu, Yaping Chi
doaj   +1 more source

A Lightweight Multi-Source Fast Android Malware Detection Model

Applied Sciences, 2022
Most of the current malware detection methods running on Android are based on signature and cloud technologies leading to poor protection against new types of malware. Deep learning techniques take Android malware detection to a new level.
Tao Peng, Bochao Hu, Junping Liu, Junjie Huang, Zili Zhang, Ruhan He, Xinrong Hu   +6 more
doaj   +1 more source

TTGNet-AMD: Android malware detection based on multi-modal feature fusion [PDF]

PeerJ Computer Science
The application of static features for Android malware detection has been extensively studied and developed. Existing methods exhibit limitations in both the completeness and discriminability of feature representation, which affects the enhancement of ...
Jiayin Feng, Meiyu Wang, JinLing Song, Chenfeng Yang, Lingzu Zhang, Yang Shen   +5 more
doaj   +2 more sources

Metaheuristics with Deep Learning Model for Cybersecurity and Android Malware Detection and Classification

Applied Sciences, 2023
Since the development of information systems during the last decade, cybersecurity has become a critical concern for many groups, organizations, and institutions.
Ashwag Albakri, Fatimah Alhayan, Nazik Alturki, Saahirabanu Ahamed, Shermin Shamsudheen   +4 more
doaj   +1 more source