Results 81 to 90 of about 11,847 (201)

2025 Japanese Heart Rhythm Society / Japanese Circulation Society Consensus Statement on the Appropriate Use of Ambulatory and Wearable Electrocardiographs

Journal of Arrhythmia, Volume 41, Issue 3, June 2025.
Recently, some clinicians have been diagnosing and treating arrhythmias on the basis of electrocardiogram (ECG) devices with low accuracy. In Europe and the US, several statements on the use of ECGs have already been published by related academic societies.
Takanori Ikeda, Takashi Ashihara, Yu‐ki Iwasaki, Maki Ono, Nobuyuki Kagiyama, Takehiro Kimura, Kengo Kusano, Ritsuko Kohno, Keita Saku, Tetsuo Sasano, Keitaro Senoo, Seiji Takatsuki, Naohiko Takahashi, Mitsuru Takami, Yukiko Nakano, Kenichi Hashimoto, Katsuhito Fujiu, Tadashi Fujino, Atsushi Mizuno, Koichiro Yoshioka, Eiichi Watanabe, Wataru Shimizu, Koichi Node   +22 more
wiley   +1 more source

Android malware detection: An eigenspace analysis approach [PDF]

2015 Science and Information Conference (SAI), 2015
7 pages, 4 figures ...
Yerima, Suleiman Y., Sezer, Sakir, Muttik, Igor   +2 more
openaire   +3 more sources

TMaD: Three‐tier malware detection using multi‐view feature for secure convergence ICT environments

Expert Systems, Volume 42, Issue 2, February 2025.
Abstract As digital transformation accelerates, data generated in a convergence information and communication technology (ICT) environment must be secured. This data includes confidential information such as personal and financial information, so attackers spread malware in convergence ICT environments to steal this information.
Jueun Jeon, Byeonghui Jeong, Seungyeon Baek, Young‐Sik Jeong   +3 more
wiley   +1 more source

Malware Detection Techniques in Android

International Journal of Computer Applications, 2015
Phones have become an important need of today. The term mobile phone and smart phone are almost identical now - a-days. Smartphone market is booming with very high speed. Smartphones have gained such a huge popularity due to wide range of capabilities they offer. Currently android platform is leading the smartphone market.
Amit Jain, Pallavi Kaushik
openaire   +1 more source

R2-D2: ColoR-inspired Convolutional NeuRal Network (CNN)-based AndroiD Malware Detections

, 2018
The influence of Deep Learning on image identification and natural language processing has attracted enormous attention globally. The convolution neural network that can learn without prior extraction of features fits well in response to the rapid ...
Huang, TonTon Hsien-De, Kao, Hung-Yu
core   +1 more source

Smart Homes of the Future

Transactions on Emerging Telecommunications Technologies, Volume 36, Issue 1, January 2025.
The advent of the Internet of Things (IoT) has revolutionized the concept of smart homes, allowing users to remotely interact with their houses. This technological development has significantly improved convenience, safety, and overall lifestyles for homeowners.
Absalom E. Ezugwu, Olutosin Taiwo, Ojonukpe S. Egwuche, Laith Abualigah, Annette Van Der Merwe, Jayanta Pal, Apu K. Saha, Ahmed Ibrahim Alzahrani, Fahad Alblehai, Japie Greeff, Micheal O. Olusanya   +10 more
wiley   +1 more source

Research on Data Mining of Permission-Induced Risk for Android IoT Devices

Applied Sciences, 2019
With the growing era of the Internet of Things (IoT), more and more devices are connecting with the Internet using android applications to provide various services.
Rajesh Kumar, Xiaosong Zhang, Riaz Ullah Khan, Abubakar Sharif   +3 more
doaj   +1 more source

Advanced hybrid malware identification framework for the Internet of Medical Things, driven by deep learning

SECURITY AND PRIVACY, Volume 8, Issue 1, January/February 2025.
Abstract The Internet of Things (IoT) effortlessly enables communication between items on the World Wide Web and other systems. This extensive use of IoTs has created new services and automation in numerous industries, enhancing the standard of living, especially in healthcare.
Ehtesham Safeer, Sidra Tahir, Asif Nawaz, Mamoona Humayun, Momina Shaheen, Maqbool Khan   +5 more
wiley   +1 more source

AMALGAN: Image‐Based Android Malware Classification Using Generative Adversarial Network

The Journal of Engineering
The Android malware detection process requires analysing numerous files to ensure system security. Malware can also be embedded in media files and images.
Zahid Hussain Qaisar, Muhammad Faheem, Muhammad Waqar Ashraf   +2 more
doaj   +1 more source

Novel Multi-Classification Dynamic Detection Model for Android Malware Based on Improved Zebra Optimization Algorithm and LightGBM

Sensors
With the increasing popularity of Android smartphones, malware targeting the Android platform is showing explosive growth. Currently, mainstream detection methods use static analysis methods to extract features of the software and apply machine learning ...
Shuncheng Zhou, Honghui Li, Xueliang Fu, Daoqi Han, Xin He   +4 more
doaj   +1 more source