AI-based modeling: techniques, applications and research issues towards automation, intelligent and smart systems

IH Sarker - SN computer science, 2022 - Springer
Artificial intelligence (AI) is a leading technology of the current age of the Fourth Industrial
Revolution (Industry 4.0 or 4IR), with the capability of incorporating human behavior and …

A comprehensive review of dimensionality reduction techniques for feature selection and feature extraction

R Zebari, A Abdulazeez, D Zeebaree, D Zebari… - Journal of Applied …, 2020 - jastt.org
Due to sharp increases in data dimensions, working on every data mining or machine
learning (ML) task requires more efficient techniques to get the desired results. Therefore, in …

Multi‐aspects AI‐based modeling and adversarial learning for cybersecurity intelligence and robustness: A comprehensive overview

IH Sarker - Security and Privacy, 2023 - Wiley Online Library
Due to the rising dependency on digital technology, cybersecurity has emerged as a more
prominent field of research and application that typically focuses on securing devices …

DroidRL: Feature selection for android malware detection with reinforcement learning

Y Wu, M Li, Q Zeng, T Yang, J Wang, Z Fang… - Computers & …, 2023 - Elsevier
Due to the completely open-source nature of Android, the exploitable vulnerability of
malware attacks is increasing. Machine learning, leading to a great evolution in Android …

Tight arms race: Overview of current malware threats and trends in their detection

L Caviglione, M Choraś, I Corona, A Janicki… - IEEE …, 2020 - ieeexplore.ieee.org
Cyber attacks are currently blooming, as the attackers reap significant profits from them and
face a limited risk when compared to committing the “classical” crimes. One of the major …

A novel permission-based Android malware detection system using feature selection based on linear regression

DÖ Şahin, OE Kural, S Akleylek, E Kılıç - Neural Computing and …, 2023 - Springer
With the developments in mobile and wireless technology, mobile devices have become an
important part of our lives. While Android is the leading operating system in market share, it …

Artificial intelligence in the cyber domain: Offense and defense

TC Truong, QB Diep, I Zelinka - Symmetry, 2020 - mdpi.com
Artificial intelligence techniques have grown rapidly in recent years, and their applications in
practice can be seen in many fields, ranging from facial recognition to image analysis. In the …

A brute-force black-box method to attack machine learning-based systems in cybersecurity

S Zhang, X **e, Y Xu - IEEE Access, 2020 - ieeexplore.ieee.org
Machine learning algorithms are widely utilized in cybersecurity. However, recent studies
show that machine learning algorithms are vulnerable to adversarial examples. This poses …

Android malware detection using machine learning with feature selection based on the genetic algorithm

J Lee, H Jang, S Ha, Y Yoon - Mathematics, 2021 - mdpi.com
Since the discovery that machine learning can be used to effectively detect Android
malware, many studies on machine learning-based malware detection techniques have …

A hybrid approach for Android malware detection using improved multi-scale convolutional neural networks and residual networks

X Fu, C Jiang, C Li, J Li, X Zhu, F Li - Expert Systems with Applications, 2024 - Elsevier
The open-source nature of Android, along with its coarse-grained permission management
and widespread use, has heightened its vulnerability to malware threats. However, many …