A systematic literature review and a conceptual framework proposition for advanced persistent threats (APT) detection for mobile devices using artificial intelligence …

AA Al-Kadhimi, MM Singh, MNA Khalid - Applied Sciences, 2023 - mdpi.com
Advanced persistent threat (APT) refers to a specific form of targeted attack used by a well-
organized and skilled adversary to remain undetected while systematically and continuously …

Convolution neural network with batch normalization and inception-residual modules for Android malware classification

TY Liu, HQ Zhang, HX Long, J Shi, YH Yao - Scientific Reports, 2022 - nature.com
Deep learning technology is changing the landscape of cybersecurity research, especially
the study of large amounts of data. With the rapid growth in the number of malware …

Explanations based on Item Response Theory (eXirt): A model-specific method to explain tree-ensemble model in trust perspective

J de Sousa Ribeiro Filho, LFF Cardoso… - Expert Systems with …, 2024 - Elsevier
Solutions based on tree-ensemble models represent a considerable alternative to real-world
prediction problems, but these models are considered black box, thus hindering their …

Android malware detection based on sensitive patterns

K Liu, G Zhang, X Chen, Q Liu, L Peng… - Telecommunication …, 2023 - Springer
In recent years, the rapid increase in the number and type of Android malware has brought
great challenges and pressure to malware detection systems. As a widely used method in …

Android malware detection based on deep learning techniques

BH Tang, Q Kang, ZX Ni, H Da, JH Xu… - 2021 4th …, 2021 - ieeexplore.ieee.org
To detect Android malware samples, a malware classification model is proposed in this
paper. traditional Android malware detection and identification techniques are usually …

Correlation matrix as a smart filter for malware classification using ensemble of novel feature selection algorithms

F Cürebal, F Demirkıran, A Çayır, H Dağ - 2023 - researchsquare.com
While the development of technology has made our lives easier, our dependence on it has
also increased. Cybercriminals develop various types of malware to exploit this …

Malware detection using machine learning on edge devices

S Parmar, C Mala - 2022 International Conference on …, 2022 - ieeexplore.ieee.org
Hackers' primary attack vectors against an IoT network are IoT nodes and edge devices. As
a result, developing practical and reliable methods for identifying malicious behavior of the …

How Reliable and Stable are Explanations of XAI Methods?

J Ribeiro, L Cardoso, V Santos, E Carvalho… - arXiv preprint arXiv …, 2024 - arxiv.org
Black box models are increasingly being used in the daily lives of human beings living in
society. Along with this increase, there has been the emergence of Explainable Artificial …

[PDF][PDF] Explanations Based on Item Response Theory (eXirt): A Model-Specific Method to Explain Tree-Ensemble Model in Trust Perspective

JSR Filhoa, LFF Cardosoa, RLS da Silvad… - researchgate.net
Solutions based on tree-ensemble models represent a considerable alternative to real-world
prediction problems, but these models are considered black box, thus hindering their …

[PDF][PDF] A Comparative Analysis of Android Malware Detection with and without Feature Selection Techniques using Machine Learning

M Ibrahim, A Abdullahi, MA Ahmad, R Mustapha - 2023 - researchgate.net
Android is an open-source operating system mainly built for smart devices to make them
easy to use and user-friendly. Thus, it has immensely engulfed other operating systems in …