Results 81 to 90 of about 2,901,102 (167)

Explaining Black-box Android Malware Detection [PDF]

2018 26th European Signal Processing Conference (EUSIPCO), 2018
Machine-learning models have been recently used for detecting malicious Android applications, reporting impressive performances on benchmark datasets, even when trained only on features statically extracted from the application, such as system calls and permissions.
Marco Melis, Davide Maiorca, Battista Biggio, Giorgio Giacinto, Fabio Roli   +4 more
openaire   +5 more sources

Securing End‐To‐End Encrypted File Sharing Services With the Messaging Layer Security Protocol

Concurrency and Computation: Practice and Experience, Volume 37, Issue 27-28, 25 December 2025.
ABSTRACT Secure file sharing is essential in today's digital environment, yet many systems remain vulnerable: if an attacker steals client keys, they can often decrypt both past and future content. To address this challenge, we propose a novel file‐sharing architecture that strengthens post‐compromise security while remaining practical.
Roland Helmich, Lars Braubach
wiley   +1 more source

A static analysis approach for Android permission-based malware detection systems.

PLoS ONE, 2021
The evolution of malware is causing mobile devices to crash with increasing frequency. Therefore, adequate security evaluations that detect Android malware are crucial.
Juliza Mohamad Arif, Mohd Faizal Ab Razak, Suryanti Awang, Sharfah Ratibah Tuan Mat, Nor Syahidatul Nadiah Ismail, Ahmad Firdaus   +5 more
doaj   +1 more source

AInsectID Version 1.1: An Insect Species Identification Software Based on the Transfer Learning of Deep Convolutional Neural Networks

Advanced Intelligent Discovery, Volume 1, Issue 2, August 2025.
This paper describes the basis for AInsectID Version 1, a GUI‐operable open‐source insect species identification, color processing, and image analysis software. This paper discusses our methods of algorithmic development, coupled to rigorous machine training used to enable high levels of validation accuracy.
Haleema Sadia, Parvez Alam
wiley   +1 more source

Leveraging Ethical Narratives to Enhance LLM‐AutoML Generated Machine Learning Models

Expert Systems, Volume 42, Issue 7, July 2025.
ABSTRACT The growing popularity of generative AI and large language models (LLMs) has sparked innovation alongside debate, particularly around issues of plagiarism and intellectual property law. However, a less‐discussed concern is the quality of code generated by these models, which often contains errors and encourages poor programming practices. This
Jordan Nelson, Michalis Pavlidis, Andrew Fish, Nikolaos Polatidis, Yannis Manolopoulos   +4 more
wiley   +1 more source

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 Applications Security [PDF]

The use of smartphones worldwide is growing very fast and also the malicious attacks have increased. The mobile security applications development keeps the pace with this trend. The paper presents the vulnerabilities of mobile applications.
Paul POCATILU
core  

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

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