Results 61 to 70 of about 2,901,102 (167)

AntiWare: An automated Android malware detection tool based on machine learning approach and official market metadata

, 2016
The prevalence of mobile devices has increased rapidly in recent years. People store valuable data like personal and financial information on those devices.
Kamil Akhuseyinoglu, Akhuseyinoglu, Kamil, Akhuseyinoglu, Nuray Baltaci, Nuray Baltaci Akhuseyinoglu   +3 more
core   +1 more source

An Effective Temporal Convolutional Networks-Based Method for Detecting Android Malware Using Dynamic Extracted Features

IEEE Access
With an increase in the number and complexity of malware, traditional malware detection methods such as heuristic-based and signature-based ones have become less adequate, leaving user applications vulnerable.
Abdurraheem Joomye, Mee Hong Ling, Muhammed Basheer Jasser, Athirah Mohd Ramly, Kok-Lim Alvin Yau   +4 more
doaj   +1 more source

Securing the Unseen: A Comprehensive Exploration Review of AI‐Powered Models for Zero‐Day Attack Detection

Expert Systems, Volume 43, Issue 3, March 2026.
ABSTRACT Zero‐day exploits remain challenging to detect because they often appear in unknown distributions of signatures and rules. The article entails a systematic review and cross‐sectional synthesis of four fundamental model families for identifying zero‐day intrusions, namely, convolutional neural networks (CNN), deep neural networks (DNN ...
Abdullah Al Siam, Nuruzzaman Faruqui, Akm Azad, Mohammad Ali Moni   +3 more
wiley   +1 more source

API Sequences based Malware Detection for Android

, 2015
To mitigate security problem brought by Android malware, various work has been proposed such as behavior based malware detection and data mining based malware detection.
Zhong Chen, Zhi Guan, Jiawei Zhu, Wu, Zhengang, Zhengang Wu, Chen, Zhong, Guan, Zhi, Zhu, Jiawei   +7 more
core   +1 more source

Analysis of Bayesian classification-based approaches for Android malware detection [PDF]

, 2013
Mobile malware has been growing in scale and complexity spurred by the unabated uptake of smartphones worldwide. Android is fast becoming the most popular mobile platform resulting in sharp increase in malware targeting the platform.
Yerima, Suleiman, Sezer, Sakir, McWilliams, G., McWilliams, Gavin, Yerima, Suleiman Y.   +4 more
core   +2 more sources

Exploiting Vision Transformer and Ensemble Learning for Advanced Malware Classification

Engineering Reports, Volume 8, Issue 1, January 2026.
Overview of the proposed RF–ViT ensemble for multi‐class malware classification. Textual (BoW/byte‐frequency) and visual representations are combined via a product rule, achieving improved accuracy and robustness over individual models. ABSTRACT Malware remains a significant concern for modern digital systems, increasing the need for reliable and ...
Fadi Makarem, Rida El Chall, Abed Ellatif Samhat, Khouloud Samrouth, Nader Bakir   +4 more
wiley   +1 more source

A review : Static analysis of android malware and detection technique

, 2021
Android malware has become more widespread in recent years due to the growing popularity of Android mobile. Android malware is installed without the user’s consent on a mobile device and exhibits significant risks to users, including personal information
Mohd Faizal, Ab Razak, Sharfah Ratibah, Tuan Mat, Ahmad Firdaus, Zainal Abidin, Juliza, Mohamad Arif, Suryanti, Awang, Nor Syahidatul Nadiah, Ismail   +5 more
core   +1 more source

A Novel Neural Network Architecture Using Automated Correlated Feature Layer to Detect Android Malware Applications

Mathematics, 2023
Android OS devices are the most widely used mobile devices globally. The open-source nature and less restricted nature of the Android application store welcome malicious apps, which present risks for such devices.
Amerah Alabrah
doaj   +1 more source

Usability Evaluation of a Push‐Based Passwordless Authentication Model Using Public‐Key Cryptography

IET Biometrics, Volume 2026, Issue 1, 2026.
Despite major advancements in the sphere of the public‐key authentication specifically in the instances of the newly established standards like WebAuthn and the FIDO2, the practical implementation of the passwordless login systems is still hindered by the usability factors, platform‐related requirements, and the very nature of the deployment process is
Ghulam Mustafa, Shah Zaman Nizamani, Irfana Memon, Asif Ali Wagan, Solomiia Fedushko, Abdullah Al Hejaili, M. Srinivas   +6 more
wiley   +1 more source

Extracting Android Applications Data for Anomaly-based Malware Detection [PDF]

, 2015
In order to apply any machine learning algorithm or classifier, it is fundamentally important to first and foremost collect relevant features. This is most important in the field of dynamic analysis approach to anomaly malware detection systems. In this
Ume U.A, Abdullahi M.B, Waziri O.V., J. Aba, Adewale O.S   +4 more
core