Results 51 to 60 of about 2,901,102 (167)
Runtime Detection Framework for Android Malware [PDF]
Mobile Information Systems, 2018 As the number of Android malware has been increased rapidly over the years, various malware detection methods have been proposed so far. Existing methods can be classified into two categories: static analysis-based methods and dynamic analysis-based methods.
TaeGuen Kim 0002 +2 more
openaire +2 more sources
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
Data Drift in Android Malware Detection
2024 International Conference on Machine Learning and Cybernetics (ICMLC)Android malware detectors are now widely implemented with machine learning algorithms, trained on large datasets of goodware and malware applications gathered at a fixed moment in time. However, as recent work showed, this domain is not stationary, causing detectors to show degrading performance over time.
Minnei, Luca +5 more
openaire +2 more sources
Android Malware Detection Using Autoencoder
CoRR, 2019 9 Pages, 4 Figures, 3 ...
Abdelmonim Naway, Yuancheng Li
openaire +3 more sources
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 +2 more
wiley +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 +4 more
wiley +1 more source
Fighting fire with fire – a Pre-emptive approach to restore control over IT assets from malware infection [PDF]
, 2012 Malware is a major threat as they induce multiple risks to infected organizations. Current Anti-Malware solutions meant to keep Malware away are challenged on how to keep the risks at bay effectively. When a Malware manages to penetrate an organization’s
Pan, J.Y.
core
Android Malware Detection Technology Based on Deep Convolutional Neural Network
四川大学学报. 自然科学版, 2020 The rapid iteration of the Android system and its open source features have resulted in many variants of Android malware, which brings great challenges to the classification and detection of Android malware.
GAO Yang-Chen +3 more
doaj
A Hybrid Approach for Android Malware Detection and Family Classification.
International Journal of Interactive Multimedia and Artificial Intelligence, 2021 With the increase in the popularity of mobile devices, malicious applications targeting Android platform have greatly increased. Malware is coded so prudently that it has become very complicated to identify.
Meghna Dhalaria, Ekta Gandotra
doaj +1 more source
Mission Aware Cyber‐Physical Security
Systems Engineering, Volume 29, Issue 2, Page 354-367, March 2026.ABSTRACT Perimeter cybersecurity, while essential, has proven insufficient against sophisticated, coordinated, and cyber‐physical attacks. In contrast, mission‐centric cybersecurity emphasizes finding evidence of attack impact on mission success, allowing for targeted resource allocation to mitigate vulnerabilities and protect critical assets.
Georgios Bakirtzis +3 more
wiley +1 more source