Results 51 to 60 of about 2,905 (223)

Machine Learning Malware Detection For Android [PDF]

, 2022
During this past year up until now, the total of malware that targets the Android operating system has increased compared to other operating systems. Therefore, an application that used the android operating system must be analyzed to detect the malware ...
Amir Muhammad Hafiz, Othman
core  

Dataset Bias in Android Malware Detection

CoRR, 2022
Researchers have proposed kinds of malware detection methods to solve the explosive mobile security threats. We argue that the experiment results are inflated due to the research bias introduced by the variability of malware dataset. We explore the impact of bias in Android malware detection in three aspects, the method used to flag the ground truth ...
Yan Lin, Tianming Liu 0002, Wei Liu, Zhigaoyuan Wang, Li Li 0029, Guoai Xu, Haoyu Wang 0001   +6 more
openaire   +2 more sources

DroidDetectMW: A Hybrid Intelligent Model for Android Malware Detection

Applied Sciences, 2023
Malicious apps specifically aimed at the Android platform have increased in tandem with the proliferation of mobile devices. Malware is now so carefully written that it is difficult to detect.
Fatma Taher, Omar AlFandi, Mousa Al-kfairy, Hussam Al Hamadi, Saed Alrabaee   +4 more
doaj   +1 more source

A Comprehensive Systematic Review of Cyber‐Physical Systems Security: Threats, Challenges, and Defense in ICS/OT Environments

Engineering Reports, Volume 8, Issue 7, July 2026.
Overview of the paper organization, illustrating the hierarchical structure of cybersecurity domains in ICS and CPS, including attack analysis, security approaches, offensive tactics, career guidance, and concluding discussions. ABSTRACT The convergence of operational technology (OT) with IP‐based information systems has exposed industrial control ...
M. A. Khalifa, Ahmad Taher Azar, Walid El‐Shafai   +2 more
wiley   +1 more source

Android Malware Detection: Looking beyond Dalvik Bytecode [PDF]

, 2021
peer reviewedMachine learning has been widely employed in the literature of malware detection because it is adapted to the need for scalability in vetting large scale samples of Android.
Tiezhu Sun, Nadia Daoudi, DAOUDI, Nadia, BISSYANDE, Tegawendé François D Assise, ALLIX, Kevin, Tegawende F. Bissyande, SUN, Tiezhu, Kevin Allix   +7 more
core   +1 more source

Static analysis framework for permission-based dataset generation and android malware detection using machine learning

EURASIP Journal on Information Security
Since Android is the popular mobile operating system worldwide, malicious attackers seek out Android smartphones as targets. The Android malware can be identified through a number of established detection techniques.
Amarjyoti Pathak, Th. Shanta Kumar, Utpal Barman   +2 more
doaj   +1 more source

GA-StackingMD: Android Malware Detection Method Based on Genetic Algorithm Optimized Stacking

Applied Sciences, 2023
With the rapid development of network and mobile communication, intelligent terminals such as smartphones and tablet computers have changed people’s daily life and work.
Nannan Xie, Zhaowei Qin, Xiaoqiang Di
doaj   +1 more source

Generating Pattern‐Based Datasets for Cyber Attack Detection Using Machine‐Learning Techniques

WIREs Data Mining and Knowledge Discovery, Volume 16, Issue 2, June 2026.
The aim of this work is to review the state of the art in the design, generation, and labeling of attack pattern datasets for training of detection systems based on machine learning. ABSTRACT This work aims to review the state of the art in the design, generation, and labeling of attack pattern datasets for the training of detection systems based on ...
Pedro Díaz García, Diego López Abril, Javier Bermejo Higuera, Víctor Gonzalez Llorente, Miguel Angel Sicilia Urbán   +4 more
wiley   +1 more source

A Study of Android Malware Detection Techniques in Virtual Environment [PDF]

, 2016
With the rapid development of mobile environment, cyber-attacks have become more commonplace and more sophisticated. In smartphone operating system market, in particular, Android platform accounts for a large portion (65% or higher).At the same time ...
정현미, 조한진, 김기봉
core  

Emulation vs Instrumentation for Android Malware Detection [PDF]

, 2019
In resource constrained devices, malware detection is typically based on offline analysis using emulation. In previous work it has been claimed that such emulation fails for a significant percentage of Android malware because well-designed malware ...
Sinha, Anukriti
core   +2 more sources